{"as_of":"2026-08-13T19:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2b62af6c952ad67b206ca039a01bb74091b03c0212eb52f9ae14e00846b56b50","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T13:54:21.916470Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.19948/citation-record","integrity":"/paper/2507.19948/integrity","json":"/paper/2507.19948/citation-record.json","paper":"/paper/2507.19948"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.676910Z","title":"A 240 180 130 db 3 s latency global shutter spatiotemporal vision sensor","venue":null,"work_id":"bedf4755-a54f-4420-9733-28c8ae02f8e9","year":2014},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:18.495440Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:7c53f86888fdee2ed89fd15c1b6a87362be48247788a3a21a6a979e8fb2b32ae","observation_id":"c0f9675d-3700-4c93-af06-71262332d20f","resolution":{"observed_at":"2026-08-06T13:54:24.681653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.659695Z","title":"Single-image depth perception in the wild","venue":null,"work_id":"84d0a506-b2e3-436a-a840-65fb7663f904","year":2016},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:18.585992Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:c076e1d5e3ed98007ff2a85720d4b4eb61425c7bbca42a0f0a3007c63314eff7","observation_id":"8324a510-352f-4816-8ce5-fab005e84dc9","resolution":{"observed_at":"2026-08-06T13:54:24.665161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.642026Z","title":"Strip attention for image restoration","venue":null,"work_id":"428326c3-5359-46d1-8418-af8b7217746f","year":2023},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:18.719847Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:c26fdb91c9b59a723c91dc956cbab145e3b243a96ec6694cbb1ac1d5c306e621","observation_id":"15d93c8a-b9be-41c2-a28f-178f2389e999","resolution":{"observed_at":"2026-08-06T13:54:24.648104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.624643Z","title":"Multi-modal fusion of event and rgb for monocular depth estimation using a unified transformer-based architecture","venue":null,"work_id":"31890956-4782-4593-b968-23bcfa3f9776","year":2024},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:18.792125Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:26a0a9443c56785678d721dd336cd42f0c6421382ab8202bd35418a99864afb8","observation_id":"cbb2f8dd-8a5b-487a-94de-5d13638aafbb","resolution":{"observed_at":"2026-08-06T13:54:24.629985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.606909Z","title":"Davit: Dual attention vision transformers","venue":null,"work_id":"59c86ebf-f13d-4889-b934-84b79811d113","year":2022},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:18.840866Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:51e462f7429cfc55bb642c8bd9ff3af3630e1db9a600466125d02380cb30453f","observation_id":"368ca4bf-e8ca-4ae0-9abe-a8d30257c1f5","resolution":{"observed_at":"2026-08-06T13:54:24.611492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.588390Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":"6d8aa806-c678-45d6-962e-7653e0edfef7","year":2020},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:18.907784Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:36d5229542d40fc2ee7b0a8b8e9a6b8add5d5e45462af75959ee2465310257ed","observation_id":"9448790d-4049-4502-b3b0-20d9eeefa82c","resolution":{"observed_at":"2026-08-06T13:54:24.593465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.568676Z","title":"Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture","venue":null,"work_id":"a4465b37-70e1-4015-aaf9-f0c46d6338e2","year":2015},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:18.963013Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:3d0e562cd57fa9ae898f9aeac13ef0afd729a18024ef9829c6b9c4a2def10c0c","observation_id":"8d9ef0e6-3740-48de-9db4-ec97e325d155","resolution":{"observed_at":"2026-08-06T13:54:24.574502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.542163Z","title":"Depth map prediction from a single image using a multi-scale deep network","venue":null,"work_id":"69490180-e9ca-4e92-856f-6920af6d46ed","year":2014},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.014577Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:00fc92e0805fd9f98da36f2888d737a9cea64c1e0b081801e0b36472d00ad86b","observation_id":"70771151-7c3d-4599-9f21-bece7d000bdb","resolution":{"observed_at":"2026-08-06T13:54:24.549931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.521114Z","title":"A unifying contrast maximization framework for event cameras, with applications to motion, depth, and optical flow estimation","venue":null,"work_id":"9b9b10d8-d04e-48c8-a3aa-eb367ea87e04","year":2018},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.087057Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:504422b006922b0d86c3b51bbbf8e4229fa5a28aca604969c31ed4b9db5fe4be","observation_id":"b2bb0fe1-8dc5-4606-b024-642e10d90f8d","resolution":{"observed_at":"2026-08-06T13:54:24.527661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.501890Z","title":"Combining events and frames using recurrent asynchronous multimodal networks for monocular depth prediction","venue":null,"work_id":"3456bd18-002a-4a52-b561-e1774ac13ab4","year":2021},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.138013Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:2c15df7a4cc14f06956bee22b94fdc18d6168afb37a969005c64b2c2e93a21f4","observation_id":"57772025-0ba4-4ab5-8d6e-c428d670c45b","resolution":{"observed_at":"2026-08-06T13:54:24.506833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.481890Z","title":"Unsupervised monocular depth estimation with left-right consistency","venue":null,"work_id":"7a9a6c7f-f72d-462b-9f82-41f90d598b79","year":2017},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.243478Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:c8b7c3b29e6205ebc3f5e4217c01c8af79e73f70bebdc4fe9ac4a055106f6ce4","observation_id":"9c40dafd-800e-44ba-91a8-d50c916414a8","resolution":{"observed_at":"2026-08-06T13:54:24.487885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.463517Z","title":"Monocular depth estimation through virtual-world supervision and real-world sfm self-supervision","venue":null,"work_id":"c61f0ba3-c46c-4d24-98d2-2fe308e4f0fa","year":2021},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.328589Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:878531e4eca7918028dbb57e2ca4af55dac5534e4834ac989e5c5b59473c948f","observation_id":"01986c6a-1be8-4c29-ad06-c3138b0dea2c","resolution":{"observed_at":"2026-08-06T13:54:24.468330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.441922Z","title":"Hierarchical neural memory network for low latency event processing","venue":null,"work_id":"608e540b-17a1-4e9d-b06c-bba3565ca24b","year":2023},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.434121Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:248148e27193f7a09857dee38081c70a3cb64528bcf8efc4ce365cdf7d3a4998","observation_id":"7b3ce649-e80a-4a4a-814d-7288aaf2433b","resolution":{"observed_at":"2026-08-06T13:54:24.450018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.420246Z","title":"Learning monocular dense depth from events","venue":null,"work_id":"946264c6-5b92-4e52-843c-66e624db38ad","year":2020},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.499536Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:2854f29df848af86524e44efc34962d88c46a88a884e9b4aa3def31e529fe8a7","observation_id":"659cd39e-a998-4e36-a0e6-6bff32b02a1f","resolution":{"observed_at":"2026-08-06T13:54:24.426551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.398712Z","title":"Look deeper into depth: Monocular depth estimation with semantic booster and attention-driven loss","venue":null,"work_id":"75e31b86-5846-4187-8797-3027db629d3d","year":2018},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.578713Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:b4046f5095a0aef4be7171efe4f59b026a2367bea2b2397754270055da5c0801","observation_id":"d0440da6-8388-422a-9cc3-2dd4825662c9","resolution":{"observed_at":"2026-08-06T13:54:24.405079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.379045Z","title":"Real-time 3d reconstruction and 6-dof tracking with an event camera","venue":null,"work_id":"208f7b5f-16f2-40b4-845d-a2cc4a4c5e93","year":2016},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.645236Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:0d1e0fde39ac8edb5869daf4e37b3ce87a60dced1bb42fc71e0230f1ca7bcfcb","observation_id":"395eef85-9f93-4922-b67a-70f41d772f05","resolution":{"observed_at":"2026-08-06T13:54:24.384808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.358389Z","title":"Multi-loss rebalancing algorithm for monocular depth estimation","venue":null,"work_id":"b0994eeb-5108-4afa-b1d7-e82ad4e7982e","year":2020},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.754790Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:b7d5b5d835f8a5dacc8ae4f956039e6879741a389e3add0effc937e7663307c3","observation_id":"564cfae4-920a-4250-bef5-fda9a59df371","resolution":{"observed_at":"2026-08-06T13:54:24.363524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.333925Z","title":"Megadepth: Learning single-view depth prediction from internet photos","venue":null,"work_id":"fc49987a-00a4-47ae-b088-1451ea955509","year":2018},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.823691Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:20e4fb5fbe35afebc848fec722c815c57da43543af4511030e1d03a05adb8a57","observation_id":"4e242f73-8786-426a-9aed-10cbb02aa668","resolution":{"observed_at":"2026-08-06T13:54:24.342417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.305032Z","title":"Srfnet: Monocular depth estimation with fine-grained structure via spatial reliability-oriented fusion of frames and events","venue":null,"work_id":"0341b879-5346-4b1a-8f39-282c07a2ac4f","year":2024},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:19.987815Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:abcfe1a2832a46bb5472d6c22e07a3a46cc7a5a5efbde5da2844488dd9981808","observation_id":"a1af8287-d36b-43f5-a3f8-ea8528c5dbce","resolution":{"observed_at":"2026-08-06T13:54:24.314053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.284801Z","title":"Vision transformers for dense prediction","venue":null,"work_id":"26f00a6a-b821-4c82-8134-dc984ea58cd8","year":2021},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.056024Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:c8d37789fa172192353f1937680366a1dbb4fcead444feb5128c810987eb79be","observation_id":"7097f92b-c3c3-40ff-b9eb-1802f64b03d5","resolution":{"observed_at":"2026-08-06T13:54:24.291487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.264949Z","title":"Emvs: Event-based multi-view stereo—3d reconstruction with an event camera in real-time","venue":null,"work_id":"7ea8db31-2e78-4f36-a730-fbb06d33a5cf","year":2018},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.156367Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:c4b463807c9c4f1a2a8960733171794d1289ab09ebd823145480f052bc4c97f2","observation_id":"b5272c4a-1857-4698-8182-7de860d9551a","resolution":{"observed_at":"2026-08-06T13:54:24.270843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.247697Z","title":"U-net: Convolutional networks for biomedical image segmentation","venue":null,"work_id":"1b61cf9a-586d-4e04-992a-aa02e8d19fca","year":2015},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.265881Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:2dd3c23a81a755ca4dcfacfd0b245926e36904623ed0624565843cf3d040822a","observation_id":"d7564038-f399-4995-afe0-98cdf72f37c4","resolution":{"observed_at":"2026-08-06T13:54:24.252975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.220396Z","title":"Event transformer","venue":null,"work_id":"f67369d6-33c1-4df8-99b5-676625e8a6b6","year":2022},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.365432Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:b65d540bca6068b686982d7ce085c38ea7c8e6fcc8c2514c4ab070d442606816","observation_id":"07662d97-8ec7-4249-a7e9-8c884291c17c","resolution":{"observed_at":"2026-08-06T13:54:24.231731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.187764Z","title":"Event transformer+","venue":null,"work_id":"8e77f51b-8828-453d-9d8e-94dc224fe0f9","year":2023},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.474938Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:5f55d9cab7d646b7cb10efb9ee9ceffe8bc736e751936882d237ffad5916f01e","observation_id":"dc54b3ba-e79f-497e-9529-94cdfd8957b8","resolution":{"observed_at":"2026-08-06T13:54:24.195205Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.154854Z","title":"Iebins: Iterative elastic bins for monocular depth estimation","venue":null,"work_id":"41ac89ef-7139-439d-bc98-7c264bd50beb","year":2024},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.535581Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:17e81fb4bb9762dbc21008979ce38fd99ac86aa22af4f1c6c20270e3d65aa9d7","observation_id":"7879a019-a545-4984-9332-a1e9ebdbb54a","resolution":{"observed_at":"2026-08-06T13:54:24.162127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.117418Z","title":"Improved event-based dense depth estimation via optical flow compensation","venue":null,"work_id":"2539a341-cf04-4768-beff-27cd091fdb24","year":2023},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.611284Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:a5aa05b239ab8e346f05b393b10efc9ab36858b84bda1a634cbcc0d81adb025f","observation_id":"7b272c49-f829-403d-b483-a35fa491de25","resolution":{"observed_at":"2026-08-06T13:54:24.135155Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.091134Z","title":"Even: An event-based framework for monocular depth estimation at adverse night conditions","venue":null,"work_id":"de54aa5d-4b19-405a-a5b6-f6710e8ac068","year":2023},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.672867Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:45e0f9d9b8fa2aac072ef9f9cb9f3d56c0f82608613d32b5d4eab8cedab4b5a3","observation_id":"6f853e6e-fbdd-49ec-a2ca-f59b10ce0be6","resolution":{"observed_at":"2026-08-06T13:54:24.096563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.072947Z","title":"Generating text with recurrent neural networks","venue":null,"work_id":"b2ba107c-d299-40a5-8b13-6936ad78b796","year":2011},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.749626Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:eb10072f3e5fe55c56df5f484a7f4c81e3c2b3db17229ca349e27640a590a76e","observation_id":"b8a12e5e-549e-425a-979d-d9073455d92e","resolution":{"observed_at":"2026-08-06T13:54:24.078796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.048485Z","title":"Perception and navigation in autonomous systems in the era of learning: A survey","venue":null,"work_id":"d87ed54f-ffba-4327-9d98-9b84535920f6","year":2022},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.816222Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:d4bc151060c0700b730b1b05593f178d833c60e7b82843db0e3ca3c0343b648e","observation_id":"3d9875b7-a1d7-4094-b04e-82cd44def8ef","resolution":{"observed_at":"2026-08-06T13:54:24.055390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:24.024356Z","title":"Learning an event sequence embedding for dense event-based deep stereo","venue":null,"work_id":"41d18ea2-8fa9-4fe3-ab7f-eb13a5d07a73","year":2019},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:20.943817Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:ef7b2562c4d0bbf48b87ac6c608cffd37cedd1c20cba20a1af1e3a0089511aa3","observation_id":"6bc0ef26-2617-4503-ba15-322acfa698e4","resolution":{"observed_at":"2026-08-06T13:54:24.030510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:23.904882Z","title":"Sdc-depth: Semantic divide-and-conquer network for monocular depth estimation","venue":null,"work_id":"60010920-ac11-4126-b47f-3cde4df4899a","year":2020},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.029434Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:bf2f13376b46977ae723ae7674cef0112e0d49c9dee0c6aab9188ab76624e01f","observation_id":"8175dc8a-ea29-4731-ac00-c99597959f1e","resolution":{"observed_at":"2026-08-06T13:54:24.009051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:23.640594Z","title":"Cliffnet for monocular depth estimation with hierarchical embedding loss","venue":null,"work_id":"0171b416-c8a0-49f2-a0c4-769f5009b2f7","year":2020},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.122488Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:a036e708f70f900c643fba5a1659faa85d36166325e61fa068dffac52f15b42f","observation_id":"7db456cb-306b-4867-b4f1-3953db1cf33f","resolution":{"observed_at":"2026-08-06T13:54:23.773161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:23.449455Z","title":"Dual transfer learning for event-based end-task prediction via pluggable event to image translation","venue":null,"work_id":"53ec97d3-de74-40e9-b595-6dafb97fe94d","year":2021},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.175892Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:376f2ba357df1fadb9189a2dc67d530e20a0c7dfcbb7cbc78b58c7a2e9dede2f","observation_id":"de09bdc8-dc9b-4512-96f2-073036791045","resolution":{"observed_at":"2026-08-06T13:54:23.521375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.13147","last_updated":"2024-11-22T09:18:20Z","snapshot_observed_at":"2026-08-12T16:44:54.490881Z","submitted_at":"2024-11-20T09:24:46Z","title":"GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation","version":2},"cited_work":{"arxiv_id":"2411.13147","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.13147","snapshot_observed_at":"2026-08-06T13:54:22.084298Z","title":"GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation","venue":"cs.CV","work_id":"5c8629b6-9a76-419c-9c33-a2f559bb1491","year":2024},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.252110Z"},"links":{"cited_paper":"/paper/2411.13147","citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:fd2121ae18bc0812cb554c87f98272fa531bb6594f4bd200089106e181758cae","observation_id":"f88ccc2c-5a77-4437-889a-a45ed1728dc2","resolution":{"observed_at":"2026-08-06T13:54:22.180959Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:23.226707Z","title":"Smooth-guided implicit data augmentation for domain generalization","venue":null,"work_id":"8aa2bf3d-40bf-4d5b-a020-c6b56ea4505f","year":2024},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.319038Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:45dc562172852d2058f9998cf7950eb50950abb4cde5105a3ba3625f485ee1fa","observation_id":"2e0b45bd-a256-4823-a8f6-3b9c539b1a3f","resolution":{"observed_at":"2026-08-06T13:54:23.305053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:23.011427Z","title":"Student becoming the master: Knowledge amalgamation for joint scene parsing, depth estimation, and more","venue":null,"work_id":"6cef144f-fb80-4c80-8555-27c76678961f","year":2019},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.460570Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:e390889d174981ae8f8c472ef5271394bf0fbb7542833d35fa033ce15b9c145d","observation_id":"da17556e-b82c-414b-a027-0e746ba14e9e","resolution":{"observed_at":"2026-08-06T13:54:23.122014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:22.828572Z","title":"Monovit: Self-supervised monocular depth estimation with a vision transformer","venue":null,"work_id":"dc7d8188-69cf-4989-949c-65cf7384bd2b","year":2022},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.541947Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:34f9f4b619263acf6f308bd68523cd31dcd343cb69540d8b276feb920b9969e4","observation_id":"867f9601-900e-400d-ba80-0260c0913551","resolution":{"observed_at":"2026-08-06T13:54:22.910782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:22.635963Z","title":"The multivehicle stereo event camera dataset: An event camera dataset for 3d perception","venue":null,"work_id":"d0b99a44-0381-4d6e-b092-ed4cb95dffd0","year":2018},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.600116Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:4c39e51ad54c819bd75a59c457d55e7ec568c661b4d88c08abbe99eacbe39d0a","observation_id":"6d9cceb2-85ec-4a99-b7a4-2519546b43b8","resolution":{"observed_at":"2026-08-06T13:54:22.705963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:22.466236Z","title":"Unsupervised event-based learning of optical flow, depth, and egomotion","venue":null,"work_id":"07db93cc-126d-4c43-9c5d-696da2545c14","year":2019},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.674297Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:cc5781912699f77fdb33b8b5244fe29c5ecf88c1697a5faa542b5d0b1a0ae735","observation_id":"5c298af5-8510-4632-bb51-89978d212d55","resolution":{"observed_at":"2026-08-06T13:54:22.556415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:22.282125Z","title":"Self-supervised event-based monocular depth estimation using cross-modal consistency","venue":null,"work_id":"46bf0daf-1c20-4bfc-989d-0a3cd709a6c7","year":2023},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.774470Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:51b646f8aa6cfbacf50b80052ac2014e63107156cc39f648a7b58131e9a41790","observation_id":"b00030da-29fb-4195-bee4-34cd08d71705","resolution":{"observed_at":"2026-08-06T13:54:22.376257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:54:21.916470Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T13:54:21.916470Z"},"links":{"citing_paper":"/paper/2507.19948"},"observation_digest":"sha256:538d21fcfd4fc422d62de3fe8946287e836ace4ade8c81f8bebd529763bb060d","observation_id":"161a1423-b1c2-46b2-b227-c960d0559eaa","resolution":{"observed_at":"2026-08-06T13:54:21.916470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.19948","last_updated":"2025-07-26T13:29:48Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T11:24:13.757331Z","submitted_at":"2025-07-26T13:29:48Z","title":"UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":1,"verified_fuzzy":39},"total_outbound_references":41},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2507.19948."}