{"as_of":"2026-08-20T14:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:01bbac9966397e5ecc02934bb75b8f0ad4be52dde8da707aa06f15b8bd7feb50","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":"2026-08-15T14:53:42.385943Z","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":"2026-08-20T06:33:59.587034+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/2608.03370/citation-record","integrity":"/paper/2608.03370/integrity","json":"/paper/2608.03370/citation-record.json","paper":"/paper/2608.03370"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:53:44.559726Z","title":"Infrared and visible image fusion methods and applica- tions: A survey,","venue":null,"work_id":"1f90bfde-d6df-49ce-bb10-1c67e5743e83","year":2019},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.577185Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:8e7396750eaa987d30fe6a24c1bcc0d433dc0a498e1e179a4af9aaf4178067e5","observation_id":"fac084c9-7b43-4be3-81d9-1b5f477a9a35","resolution":{"observed_at":"2026-08-15T14:53:44.593662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:44.391271Z","title":"Cross- modality interactive attention network for multispectral pedestrian de- tection,","venue":null,"work_id":"6ba56563-039e-49da-8da3-7c0ee77621a2","year":2019},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.581232Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:d4b52c2d7cbd85f7e6f832cda1d51d087df05b1f927c4aa98042992849480357","observation_id":"632a120a-c7d2-4a86-9c26-a2cfba53908f","resolution":{"observed_at":"2026-08-15T14:53:44.456358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:44.290260Z","title":"Improving multispectral pedestrian detection by addressing modality imbalance problems,","venue":null,"work_id":"74d4fd64-1168-47b4-9009-d29868a2c618","year":2020},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.585470Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:fc42d84250bb07457e2f2aec710b0743bb85a63a2a6c7e3fd3366ffecbd8068c","observation_id":"d6b236e6-b163-4f14-bde2-f9c046149246","resolution":{"observed_at":"2026-08-15T14:53:44.294010Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:44.280058Z","title":"Illumination-aware faster R- CNN for robust multispectral pedestrian detection,","venue":null,"work_id":"f6bca2d7-e74b-461c-a8a2-90e37a6861e3","year":2019},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.595564Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:2fd4d8fc331a5ed342f2b402933e2d8e477043801465e840f7869697df3755db","observation_id":"6238fa50-076e-4c2a-85f6-e2d3149979be","resolution":{"observed_at":"2026-08-15T14:53:44.283412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:44.269861Z","title":"HAFNet: Hierarchical attentive fusion network for multispectral pedestrian detection,","venue":null,"work_id":"5cb5c580-c46c-4a3b-8b02-a5aaf06362dc","year":2023},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.600086Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:444948f4d30de6ddec269dd92f277c1d860aa9e5f22659a9cb9e3dbbe7d3f531","observation_id":"52aaf084-f1e4-4c2d-b257-12ff9813a848","resolution":{"observed_at":"2026-08-15T14:53:44.273800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:44.187088Z","title":"Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection,","venue":null,"work_id":"2c4a90a8-6aed-4087-9564-abeabba11672","year":2022},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.604463Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:c045a8a1b8f6a3dabc359a24ec5da4af9315d17c2c4d6dd1967732ba6b1d66d1","observation_id":"db3edf93-f23f-4b43-b81b-7d44bed65e58","resolution":{"observed_at":"2026-08-15T14:53:44.262418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:44.000652Z","title":"High performance RGB-thermal video object detection via hybrid fusion with progressive interaction and temporal-modal difference,","venue":null,"work_id":"5e140b10-536b-4d92-9d83-81becbca7841","year":2025},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.608360Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:0508941b5d20e3393d46c78ee618dc932be3aa35a21e8ccfe7a265299c17e007","observation_id":"2c947b65-994d-43fa-8acf-039ae3749a1e","resolution":{"observed_at":"2026-08-15T14:53:44.087560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.954194Z","title":"Guided attentive feature fusion for multispectral pedestrian detection,","venue":null,"work_id":"a9d18b96-37ca-4eb4-b6aa-ea9b6bc9b7b9","year":2021},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.612076Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:ba7a8309f627f3ea9508483b5ea996232b84274a8d2db886fedae24f756b7725","observation_id":"c166a845-6267-423f-bf2f-191474e3d6d1","resolution":{"observed_at":"2026-08-15T14:53:43.958011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.942973Z","title":"ICAFusion: Iterative cross-attention guided feature fusion for multispectral object detection,","venue":null,"work_id":"ff672e49-7c0c-404c-ad36-9a51d566e7c3","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.616497Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:17d5facf7d1d021552186b0d2e9cc1789357d1d136a99d902d3ccc590f033713","observation_id":"8723bf2f-9350-4353-8c1f-ebdda13cda14","resolution":{"observed_at":"2026-08-15T14:53:43.947559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.931277Z","title":"Multidimensional fusion network for multispectral object detection,","venue":null,"work_id":"c091a2eb-8d10-4be8-95cb-f5185c2823e5","year":2025},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.621224Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:ed721e064cbe5cee3999140a5bd7e9d551c85a066390010f8df5b1b028ecfc48","observation_id":"2b96dc08-1fb4-4973-8e18-54cca639dfbe","resolution":{"observed_at":"2026-08-15T14:53:43.935284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.919373Z","title":"MCFusion: Frequency domain characteristics enhancement and feature compensation fusion network for RGB-T object detection,","venue":null,"work_id":"785ac0f7-252c-4d10-8bcb-625f77068ff3","year":2025},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.624657Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:bb1f7d97a4ccb0ec6dba8495a884192b2cc71f1d46866b0af41fd221e67da4af","observation_id":"72583429-2828-4dfc-b753-f0a774f27d30","resolution":{"observed_at":"2026-08-15T14:53:43.924008Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.15491","last_updated":"2025-05-21T13:17:57Z","snapshot_observed_at":"2026-08-07T15:14:26.187104Z","submitted_at":"2025-05-21T13:17:57Z","title":"Spectral-Aware Global Fusion for RGB-Thermal Semantic Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.15491","snapshot_observed_at":"2026-08-15T14:53:41.628087Z","title":"Spectral-aware global fusion for RGB-thermal semantic segmentation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.628087Z"},"links":{"cited_paper":"/paper/2505.15491","citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:d7955e285a9dd7b287e098e4bfc4ea799a276a2a2fbd8d63e396abbee98e7b67","observation_id":"9121dfc5-599f-48f0-b91c-a2ffde0cb546","resolution":{"observed_at":"2026-08-15T14:53:41.628087Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:53:43.728412Z","title":"Multimodal object detection by channel switching and spatial attention,","venue":null,"work_id":"955a6fbb-c133-4227-a9ff-fb16c7c8d835","year":2023},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.633148Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:b8bddf12ce826c06946ce0d7971a49731e528c1c662747976dbb2dd88314c4f8","observation_id":"fa2f5c81-80e4-40c6-ba3e-2d9d3ccf6774","resolution":{"observed_at":"2026-08-15T14:53:43.855543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.654452Z","title":"Multi-scale aggregation transformers for multispectral object detection,","venue":null,"work_id":"8dd41670-c52c-4085-8421-f3c6c816fa9b","year":2023},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.637532Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:515e0c466924a527d0c3bb02fa69c4bd53f0ae0c2cbe24c9ace708515c0f11fe","observation_id":"7784dff5-9c18-4df0-be89-939f96d4f801","resolution":{"observed_at":"2026-08-15T14:53:43.658720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.643815Z","title":"CDDFuse: Correlation-driven dual-branch feature decomposition for multi-modality image fusion,","venue":null,"work_id":"7587e3d2-fdb7-4743-89ad-40fd96725e0f","year":2023},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.684496Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:be411ee33af9acf5b98b92e402615e24adf714172e543c281e6ea4e74473faf4","observation_id":"418e3c19-c802-4c99-aba8-3c87035fa02a","resolution":{"observed_at":"2026-08-15T14:53:43.646925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.502066Z","title":"CrossFormer: Cross-guided attention for multi-modal object detection,","venue":null,"work_id":"a098682b-32e6-455b-84b6-71e0c27d55ff","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.736528Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:1913027425ab97ad3e5839bd96c71ece7dcb2fc2be67a8e64a5b074f81c7f476","observation_id":"c2b2c1f0-2c0a-4a6d-8882-d08fa49c3088","resolution":{"observed_at":"2026-08-15T14:53:43.636237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.307111Z","title":"Fusion- Mamba for cross-modality object detection,","venue":null,"work_id":"e397c3fa-0f88-42e7-92aa-0591472f27fc","year":2025},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.790668Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:93a12001cab135ef5d8dffd91e1c0a523036794e6d29434d0639f52db50c72be","observation_id":"293f204a-59da-4ce8-94a0-1855a72bb376","resolution":{"observed_at":"2026-08-15T14:53:43.364731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.296593Z","title":"WaveMamba: Wavelet-driven mamba fusion for RGB-infrared object detection,","venue":null,"work_id":"947b3081-beb1-466f-82de-74ef928976ba","year":2025},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.936445Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:0c94bd192e181022700e4ac593ec3239cf2ef8071d693244860f0411dbb17c23","observation_id":"3559020b-a542-4061-8753-70193d0bf438","resolution":{"observed_at":"2026-08-15T14:53:43.300567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.286404Z","title":"Improving RGB- infrared object detection with cascade alignment-guided transformer,","venue":null,"work_id":"536a2c82-2e5a-42ea-a0ab-6345ecce8a0a","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.940805Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:f92dc5c78b40e686d64e057037749a7e84280134d0ac5b5248983b774af7b2a6","observation_id":"9726e183-4e95-441c-ac9c-c6d6b547db0f","resolution":{"observed_at":"2026-08-15T14:53:43.290396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:41.944820Z","title":"Removal then selection: A coarse-to-fine fusion perspective for RGB-infrared object detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.944820Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:13b6b51135029e2409431c74c078efcf6403c9bf373239555bc609e87c5ab1e9","observation_id":"abb2c9e1-8f10-4646-afbb-a916d62b3ca6","resolution":{"observed_at":"2026-08-15T14:53:41.944820Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:53:43.274661Z","title":"Optimal operators in digital image processing,","venue":null,"work_id":"2c7fc8c9-e43a-45e2-b489-94a86af57077","year":2000},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.949120Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:b91f7d7a7a1c0f3947f4785892043add64905731f256b664d7eeba59a72bb076","observation_id":"ead739fb-64d0-474f-a4d3-0f222b864965","resolution":{"observed_at":"2026-08-15T14:53:43.279188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.264020Z","title":"YOLO11 by ultralytics,","venue":null,"work_id":"8bc7f6d1-b18c-4ea8-a211-b440e184e2a4","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.952823Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:3e11a5d661d91e0d13dcb662f156e92914fab044d962c3ceef9ba772de2a4020","observation_id":"acd65627-97cf-45bd-b028-6bbd6d777a33","resolution":{"observed_at":"2026-08-15T14:53:43.267874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:43.045273Z","title":"Feature pyramid networks for object detection,","venue":null,"work_id":"c4c5fe11-3a16-4ded-8ff6-af2a78166dd7","year":2017},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.956636Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:c35c2dc9d8af33c0bf058ab2dd7822abf19a1cc705aec1d78a641ef20b1e50f2","observation_id":"df36bdd4-fe4f-48ed-9680-43b7431a10cc","resolution":{"observed_at":"2026-08-15T14:53:43.098065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.03775","last_updated":"2025-03-01T15:41:19Z","snapshot_observed_at":"2026-08-16T12:59:30.351881Z","submitted_at":"2025-01-07T13:30:54Z","title":"Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.03775","snapshot_observed_at":"2026-08-15T14:53:41.960395Z","title":"Strip R-CNN: Large strip convolution for remote sensing object detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.960395Z"},"links":{"cited_paper":"/paper/2501.03775","citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:ec56c59bd4610321cb59b12d4f3fe1b53e7faf6134bddf788be3fecc6f5c82e3","observation_id":"e1116c9d-fd54-4f8b-b08b-0853e79300de","resolution":{"observed_at":"2026-08-15T14:53:41.960395Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.00273","last_updated":"2022-10-04T09:52:39Z","snapshot_observed_at":"2026-08-19T03:49:55.080409Z","submitted_at":"2021-10-30T15:34:12Z","title":"Cross-Modality Fusion Transformer for Multispectral Object Detection","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.00273","snapshot_observed_at":"2026-08-15T14:53:41.964966Z","title":"Cross-modality fusion transformer for multispectral object detection,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.964966Z"},"links":{"cited_paper":"/paper/2111.00273","citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:46a64161bc6b9689cb40beb6c4b0131d220e7c340e37b1b60a4dbb954017f9dc","observation_id":"5c68fa11-911e-42e1-96b0-81e6c9e56558","resolution":{"observed_at":"2026-08-15T14:53:41.964966Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:53:42.920801Z","title":"MetaFusion: Infrared and visible image fusion via meta-feature embedding from object detection,","venue":null,"work_id":"9b753cce-d7c4-49e1-92f1-be74a8e2f142","year":2023},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.968794Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:aabc57dae8263bec7ea63e40a456609b53c5d0ae3e1cb215fe78f8a41b5ab91a","observation_id":"3d684d23-ea6b-4bad-afe4-b3a2d3b76cee","resolution":{"observed_at":"2026-08-15T14:53:42.984276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.863274Z","title":"Diff-IF: Multi-modality image fusion via diffusion model with fusion knowledge prior,","venue":null,"work_id":"c6bfee9e-d781-4285-8f6c-6654a7e3c09e","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.971995Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:b43676d5b8e345cc939620e2ea5b0a7fc9f1afeab539d44abbf0d0dbe653f18b","observation_id":"e35e66ca-8bec-485a-bdfb-b6b9607c383e","resolution":{"observed_at":"2026-08-15T14:53:42.866571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.851753Z","title":"CAMF: An interpretable infrared and visible image fusion network based on class activation mapping,","venue":null,"work_id":"fdcb0e90-4cb3-422e-b050-3867ffd24865","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.975706Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:3962a9bb9a9b1c5df2d93661beeb3dcca5c50805af93a5d39cc4d1c038f2ea03","observation_id":"b9ffb87a-5340-400c-ba2b-35b84297e339","resolution":{"observed_at":"2026-08-15T14:53:42.855152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.840877Z","title":"YOLO-Adaptor: A fast adaptive one-stage detector for non-aligned visible-infrared object detection,","venue":null,"work_id":"df154e0c-438b-4cd0-8b8e-e87d15b86ee6","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.980167Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:3f3f54e6e39714e1c67330cea33ac1eadb5e180bc315e27894d4391b4f3e6447","observation_id":"019430ca-5440-4fd4-8923-df59d95d3c67","resolution":{"observed_at":"2026-08-15T14:53:42.844958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.829632Z","title":"ACDF-YOLO: Attentive and cross-differential fusion network for multimodal remote sensing object detection,","venue":null,"work_id":"d63e2df7-9305-4820-adbf-79915f81596d","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.983911Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:dfc4f75b3f571c6a85849bd10e8206c6b349685116247e2e3bac2597cbf66075","observation_id":"36d0bc66-2229-4952-8009-0dce55d385e0","resolution":{"observed_at":"2026-08-15T14:53:42.833366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.817345Z","title":"A dual-modality pedestrian detection method based on multi-scale feature fusion,","venue":null,"work_id":"6f4bb1be-a74c-46b3-8eb9-1f5f005fc8f4","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.987928Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:8c326fc5858a3b9e3905896d8c7a33417cabf177701ecd6b2fdc58ee4c4c1e2d","observation_id":"25d3abff-d218-4aae-a415-603ffe5dfcfb","resolution":{"observed_at":"2026-08-15T14:53:42.821869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.805584Z","title":"TFDet: Target-aware fusion for RGB-T pedestrian detection,","venue":null,"work_id":"1fcd3619-0dc0-43a2-8550-bf73d91d5d11","year":2025},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.991613Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:4d9655272851722266a932bcea1d9210c86be851f7bff8dcb8421ac372228ea8","observation_id":"43958127-08b0-41f8-a43f-730af24058cd","resolution":{"observed_at":"2026-08-15T14:53:42.809372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.793796Z","title":"Explicit attention-enhanced fusion for RGB-thermal perception tasks,","venue":null,"work_id":"56c5201d-183c-4b0f-a06e-c1aa762ab5be","year":2023},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.995421Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:b03fefdfb6155acbc1a547983242cd09c023a8db3fe5a9f90d23dbe389822fc5","observation_id":"7eb1a0a2-0940-4501-abac-c3bb4a98147e","resolution":{"observed_at":"2026-08-15T14:53:42.797954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.781723Z","title":"LLVIP: A visible-infrared paired dataset for low-light vision,","venue":null,"work_id":"179731c1-694e-4073-a87f-11982f8f796c","year":2021},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:41.998975Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:d5c39a2e7f8f9f669506a72498e13cbc1a37ed406e1c543ef0fc739dfd1f2a37","observation_id":"04f0bf57-f17b-464a-8b8d-778cb31b57e9","resolution":{"observed_at":"2026-08-15T14:53:42.785887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.575820Z","title":"SuperFusion: A ver- satile image registration and fusion network with semantic awareness,","venue":null,"work_id":"fd947d05-1426-434b-aee2-6ad6a187f85d","year":2022},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:42.002284Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:8448c25eb74ef256843620330249fffda8456b647e278f0295011ffb454ad0ed","observation_id":"a27e6f8d-5d5e-4d17-90e5-2ac877980071","resolution":{"observed_at":"2026-08-15T14:53:42.637913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.564563Z","title":"Learning a graph neural network with cross modality interaction for image fusion,","venue":null,"work_id":"b91a3da2-eabf-4beb-b00d-838bf0320c98","year":2023},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:42.047272Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:321e9fe1419a88b598640e25f0741d99623da03c0cf603cb0a3062f4bb56c712","observation_id":"8005fc5a-b0cb-43f5-85fb-302777a58f6f","resolution":{"observed_at":"2026-08-15T14:53:42.568291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.101428Z","title":"KCDNet: Multimodal object detection in modal information imbalance scenes,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:42.101428Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:a961e7f7c0018cf1757d7e36fe8348895791f6cdc3e3064475101abcfe42228e","observation_id":"73752ff1-12fe-4d65-aa27-6b30a72aaa99","resolution":{"observed_at":"2026-08-15T14:53:42.101428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:53:42.546435Z","title":"MRD-YOLO: A multi- spectral object detection algorithm for complex road scenes,","venue":null,"work_id":"7d6bc689-a760-44f0-8a04-27434f0743e7","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:42.158597Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:f47cb6fb0d66335eaedc7e1c946ba5a5b05314c8d8fe19d70617f7d0e08cbfa5","observation_id":"ecdec449-3f8f-457a-95c5-9ad3e991dc00","resolution":{"observed_at":"2026-08-15T14:53:42.550850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.534355Z","title":"Cross-modal oriented object detection of UA V aerial images based on image feature,","venue":null,"work_id":"a75ef7c1-7000-4d8c-8ec3-c333c625579a","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:42.297957Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:febe282c50273e9c8d09bc26ca448b0cea9ac64b63104115d4a556e9a0b0bc40","observation_id":"2654908d-afdb-4e7f-804a-1840c356e6e6","resolution":{"observed_at":"2026-08-15T14:53:42.538344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.523569Z","title":"Equivariant multi-modality image fusion,","venue":null,"work_id":"9d68933c-0c0b-4ed5-966e-798492bfbc1a","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:42.381622Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:e2cbd62b18cfcb5d83561e74b9db5df05878f363e68a6d5b0e2dfe0e19bc1eaa","observation_id":"87a6396f-e8d9-437c-a3ba-6d171883d8c7","resolution":{"observed_at":"2026-08-15T14:53:42.526970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-15T14:53:42.510308Z","title":"RGB-IR YOLO combining modality-specific reconstruction and information integration,","venue":null,"work_id":"a4e3d3a4-0858-4e1d-a83a-fd1283378be5","year":2024},"citing_paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T14:53:42.385943Z"},"links":{"citing_paper":"/paper/2608.03370"},"observation_digest":"sha256:7628fefe4bbe5b471a268b43638ae4a7b63232e04bd10839e039bb041a53170f","observation_id":"6a735b47-fea3-4888-a342-9ffa22c4b7b5","resolution":{"observed_at":"2026-08-15T14:53:42.515779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2608.03370","last_updated":"2026-08-04T09:20:31Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-18T15:01:58.138850Z","submitted_at":"2026-08-04T09:20:31Z","title":"DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":0,"verified_fuzzy":36},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2608.03370."}