{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","short_pith_number":"pith:ZNPBJ5MS","canonical_record":{"source":{"id":"2607.08771","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-09T17:59:58Z","cross_cats_sorted":[],"title_canon_sha256":"913cc9bb32a8a59a036aab62f79a948520233817f091c2c09ec7612955ad302d","abstract_canon_sha256":"c2df81c4c899bd31880e05872a523653398f8582ee14ac773af152fad155b89c"},"schema_version":"1.0"},"canonical_sha256":"cb5e14f5925fb9c889429bc108b24f91bcd41c0f12f3a3f4d781118a0c74c0d4","source":{"kind":"arxiv","id":"2607.08771","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.08771","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"arxiv_version","alias_value":"2607.08771v1","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.08771","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"pith_short_12","alias_value":"ZNPBJ5MSL644","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZNPBJ5MSL644RCKC","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZNPBJ5MS","created_at":"2026-07-10T01:19:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"record","payload":{"canonical_record":{"source":{"id":"2607.08771","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-09T17:59:58Z","cross_cats_sorted":[],"title_canon_sha256":"913cc9bb32a8a59a036aab62f79a948520233817f091c2c09ec7612955ad302d","abstract_canon_sha256":"c2df81c4c899bd31880e05872a523653398f8582ee14ac773af152fad155b89c"},"schema_version":"1.0"},"canonical_sha256":"cb5e14f5925fb9c889429bc108b24f91bcd41c0f12f3a3f4d781118a0c74c0d4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-10T01:19:59.865508Z","signature_b64":"guiKB6HUmoRPsbUSOCA/20iAOnp2WME1jfZWzYxk4UfORcrZY5RA5GCdnULKvX2eiM4/sQ9GIOxIVtSwLO1oBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cb5e14f5925fb9c889429bc108b24f91bcd41c0f12f3a3f4d781118a0c74c0d4","last_reissued_at":"2026-07-10T01:19:59.865084Z","signature_status":"signed_v1","first_computed_at":"2026-07-10T01:19:59.865084Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.08771","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T01:19:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G39mnoazJh5t29PzWK08VylbVV6fROBwnY+alVdJY7g+/Q5wrebBBgCg2p5LbqasCvomfIgq5Q9fy5exvELHAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.913033Z"},"content_sha256":"59e2d735b86f0917b4c8003c0233ac8ca10da65beee85a3547ce61453511996f","schema_version":"1.0","event_id":"sha256:59e2d735b86f0917b4c8003c0233ac8ca10da65beee85a3547ce61453511996f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fabio Tosi, Luca Bartolomei, Matteo Poggi, Stefano Mattoccia","submitted_at":"2026-07-09T17:59:58Z","abstract_excerpt":"Monocular depth estimation has seen remarkable progress through foundation models achieving robust zero-shot generalization, yet their computational demands place them far beyond the reach of embedded and mobile platforms. Lightweight alternatives exist, but have been developed almost exclusively within single-domain, self-supervised paradigms, failing silently under domain shift. We present ZipDepth, a compact monocular depth network that bridges this gap by combining an efficient reparameterizable encoder-decoder with large-scale knowledge distillation from a foundation model over a large mu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.08771","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.08771/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T01:19:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jGbOZnp+SFhg3YCStwG6SZcG1q6XNA8lP8EZwGat4xod/LCR5vpu1yzNur8ivh8H6a3YTWH+fMbQ+C8GyQPPBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.913429Z"},"content_sha256":"6ce59600e71f5d532864135249c02a398c0ed3e563de0342b14de27cfd76a93f","schema_version":"1.0","event_id":"sha256:6ce59600e71f5d532864135249c02a398c0ed3e563de0342b14de27cfd76a93f"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"integrity","payload":{"note":"URL 'https://github.com/ultralytics/yolov58' returned status 404 (Not Found) at last check.","snippet":null,"arxiv_id":"2607.08771","detector":"external_links","evidence":{"url":"https://github.com/ultralytics/yolov58","final_url":"https://github.com/ultralytics/yolov58","host_kind":"github","status_code":404,"status_text":"Not Found","verdict_class":"incontrovertible","checked_at_unix":1783661622.388805},"severity":"critical","ref_index":null,"audited_at":"2026-07-10T05:33:42.645870Z","event_type":"pith.integrity.v1","detected_doi":null,"detector_url":"https://pith.science/pith-integrity-protocol#external_links","external_url":"https://github.com/ultralytics/yolov58","finding_type":"dead_code_link","evidence_hash":"76e09dce5feb17bf5233e6b6b987fd68e744da727b085b377eabdd79d61e4485","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":11845,"payload_sha256":"2228819d1eff7d894abbddac4c9d1ed4236b588864151f666ac2ba2ca24b68dd","signature_b64":"t2fn2MTaQKLgJ3wG2CMiqKzsZUXXNx1Nhj3bbtSJdBTJLMk/zo3aroIBoRSOP6pm+ZL7tuFAp13Lx3QEBqsxAA==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T05:33:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3vqZyyJRt9Qu0SMoUe7JnTiVHcskHD5QzphJRapM1iyEuRdJtVzEXntsxmCffKfJU5CW4dIggR9RLFgnK4/jBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.915361Z"},"content_sha256":"96ff387ec1f47ca0841a7cd68c02838e4af660b4d9c7c0cccbb6b1328a677b6b","schema_version":"1.0","event_id":"sha256:96ff387ec1f47ca0841a7cd68c02838e4af660b4d9c7c0cccbb6b1328a677b6b"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"integrity","payload":{"note":"Identifier '10.1109/cvpr.2017.7002' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Zhou, T., Brown, M., Snavely, N., Lowe, D.G.: Unsupervised Learning of Depth and Ego-Motion from Video. Conference on Computer Vision and Pattern Recog- nition pp. 6612–6619 (2017).https://doi.org/10.1109/CVPR.2017.7002, 4","arxiv_id":"2607.08771","detector":"doi_compliance","evidence":{"doi":"10.1109/cvpr.2017.7002","arxiv_id":null,"ref_index":108,"raw_excerpt":"Zhou, T., Brown, M., Snavely, N., Lowe, D.G.: Unsupervised Learning of Depth and Ego-Motion from Video. Conference on Computer Vision and Pattern Recog- nition pp. 6612–6619 (2017).https://doi.org/10.1109/CVPR.2017.7002, 4","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"]},"severity":"critical","ref_index":108,"audited_at":"2026-07-10T01:41:31.321281Z","event_type":"pith.integrity.v1","detected_doi":"10.1109/cvpr.2017.7002","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"447a21404cb5305ae11eabd8cdc28a1f5e9d55d7ba577add408723df2b6102ec","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":11739,"payload_sha256":"1b461448d318a067d6c29f88143515886e62c9c9218733ebf7a82c07a9d539a4","signature_b64":"3OwOU5zcyEfQge9x/jl66mAibpPOnyYJQPwn6HrcXHHWV1Hc5WbbJ3+txQUEOXm7QRzZPCOQDWjItFR4y/YzCA==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T01:43:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nUVH/f8GeECVS4g57VMBXlUiy46kHe9+kCOU0y+VrPnUWCL2yBya9texU3NNzzCmA7KxYkVT3CdqA+WIHONjCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.915697Z"},"content_sha256":"e8b22b9441c30900adce806e75039877f81c11c5d042bf71d3d056ef029659bb","schema_version":"1.0","event_id":"sha256:e8b22b9441c30900adce806e75039877f81c11c5d042bf71d3d056ef029659bb"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"integrity","payload":{"note":"Identifier '10.1109/cvpr.2018.000434' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Zhan, H., Garg, R., Weerasekera, C.S., Li, K., Agarwal, H., Reid, I.M.: Unsuper- vised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction. Conference on Computer Vision and Pattern Recognition pp. 34","arxiv_id":"2607.08771","detector":"doi_compliance","evidence":{"doi":"10.1109/cvpr.2018.000434","arxiv_id":null,"ref_index":103,"raw_excerpt":"Zhan, H., Garg, R., Weerasekera, C.S., Li, K., Agarwal, H., Reid, I.M.: Unsuper- vised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction. Conference on Computer Vision and Pattern Recognition pp. 340–349 (2018).https://doi.org/10.1109/CVPR.2018.000434","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"]},"severity":"critical","ref_index":103,"audited_at":"2026-07-10T01:41:31.321281Z","event_type":"pith.integrity.v1","detected_doi":"10.1109/cvpr.2018.000434","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"850325677a103b349edad4cdfd8bafb6948cfe247a3901f1c16870a60e5d419b","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":11738,"payload_sha256":"3361bb22f5cea791fc695e433d0de6dad21499f96ce4c26721da09ba581d64a1","signature_b64":"oSWtRTHgM38Vw4oq0B9qRbXpmX2M81Vtv1MMwZfitmGU72WLQMan8fm48lK4P8Z88FOCOsjVgMgL5iwOS6HBDg==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T01:43:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4hSMZPtU4D0Nzg7imxPOuldiPEZ08t2y7qHKyN1oCs2jZeX92jVcfq+CqdEutx9Y83qcUDNSHk0Wxcv94TEwDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.915992Z"},"content_sha256":"f4d0a6a8ff036495ab68610aaa079f32201c3c5f704b3551d1b1c6a1dfc0d2a5","schema_version":"1.0","event_id":"sha256:f4d0a6a8ff036495ab68610aaa079f32201c3c5f704b3551d1b1c6a1dfc0d2a5"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"integrity","payload":{"note":"Identifier '10.1109/cvpr52688.2022.003894' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Yuan, W., Gu, X., Dai, Z., Zhu, S., Tan, P.: Neural window fully-connected crfs for monocular depth estimation. In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3906–3915 (2022).https://doi. org/10.1109/CV","arxiv_id":"2607.08771","detector":"doi_compliance","evidence":{"doi":"10.1109/cvpr52688.2022.003894","arxiv_id":null,"ref_index":100,"raw_excerpt":"Yuan, W., Gu, X., Dai, Z., Zhu, S., Tan, P.: Neural window fully-connected crfs for monocular depth estimation. In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3906–3915 (2022).https://doi. org/10.1109/CVPR52688.2022.003894","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"]},"severity":"critical","ref_index":100,"audited_at":"2026-07-10T01:41:31.321281Z","event_type":"pith.integrity.v1","detected_doi":"10.1109/cvpr52688.2022.003894","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"8727a7e1302901c128265c4b3d8b64305abeaf5375646914e5870ae8296000f3","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":11737,"payload_sha256":"61e1a2f63d549ef1f9f7a5393d83bd0e7d538fb73018ee6044c1c8d5ae9bd0f0","signature_b64":"YQqdrLo9GqUqps1cvKu00l7jOxyewJVm+H5G8Cu3/GO2lMPx+5S49JST2nCxLMhm80o/YleJ1AMOcu7vkprBDQ==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T01:43:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jdGGpOOKDCBuHk+T1ZZjbuiLlQCFOmEHO1uw2vwMPulWSEEiDa8iOiWO9+o/HNm/YXauOoS5NC4FI+xUfbSVBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.916280Z"},"content_sha256":"9adcd4793078689da7ed13cbdea1fb1e24a2f9ae047f0f03daff7287fc6224e7","schema_version":"1.0","event_id":"sha256:9adcd4793078689da7ed13cbdea1fb1e24a2f9ae047f0f03daff7287fc6224e7"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1109/ICCV.2019.002254) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Watson, J., Firman, M., Brostow, G., Turmukhambetov, D.: Self-supervised monocular depth hints. In: 2019 IEEE/CVF International Conference on Com- puter Vision (ICCV). pp. 2162–2171 (2019).https://doi.org/10.1109/ICCV. 2019.002254","arxiv_id":"2607.08771","detector":"doi_compliance","evidence":{"ref_index":88,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"Watson, J., Firman, M., Brostow, G., Turmukhambetov, D.: Self-supervised monocular depth hints. In: 2019 IEEE/CVF International Conference on Com- puter Vision (ICCV). pp. 2162–2171 (2019).https://doi.org/10.1109/ICCV. 2019.002254","reconstructed_doi":"10.1109/ICCV.2019.002254"},"severity":"advisory","ref_index":88,"audited_at":"2026-07-10T01:41:31.321281Z","event_type":"pith.integrity.v1","detected_doi":"10.1109/ICCV.2019.002254","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"47c215ddade8c74247f5c0227522152fcaf0284c6928c3ae5c5e3939af2436b7","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":11736,"payload_sha256":"47631657ac063cffb5b5f9a0f512e257fd89a76a27503aab999654b627c2b69f","signature_b64":"fZWVlJ5qudU+7INrOlzqZDuG/ISMShDyXiT8DuVOAdmZ+HaG4flBZ2sQQTd2uN362JbnsElHS9nIsDTQQ8oNBA==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T01:43:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v4CRA4nHzlagQCFgmNA6+dJ19GtRr7BxddKgMmMgR3hZpe5MyvI1boY3is3BLgcUJw2BNqccRbrbW1NSGVHsBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.916575Z"},"content_sha256":"f2d0af0a6db5a4982448f7f76e7855f66e0f5436abf45f734e0da9a04ca4ce64","schema_version":"1.0","event_id":"sha256:f2d0af0a6db5a4982448f7f76e7855f66e0f5436abf45f734e0da9a04ca4ce64"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"integrity","payload":{"note":"Identifier '10.1109/cvpr.2017.6994' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Godard, C., Aodha, O.M., Brostow, G.J.: Unsupervised Monocular Depth Esti- mation with Left-Right Consistency. Conference on Computer Vision and Pattern Recognition pp. 6602–6611 (2017).https://doi.org/10.1109/CVPR.2017.6994","arxiv_id":"2607.08771","detector":"doi_compliance","evidence":{"doi":"10.1109/cvpr.2017.6994","arxiv_id":null,"ref_index":26,"raw_excerpt":"Godard, C., Aodha, O.M., Brostow, G.J.: Unsupervised Monocular Depth Esti- mation with Left-Right Consistency. Conference on Computer Vision and Pattern Recognition pp. 6602–6611 (2017).https://doi.org/10.1109/CVPR.2017.6994","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"]},"severity":"critical","ref_index":26,"audited_at":"2026-07-10T01:41:31.321281Z","event_type":"pith.integrity.v1","detected_doi":"10.1109/cvpr.2017.6994","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"9189a44b91456c88c3daac472acd60bd246f6899ff43dadc3d488a9546b8c0de","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":11735,"payload_sha256":"57c3dfd2d09f516066a26611da4bee1744769ca3fc28d54bef45b8ddc9a318bd","signature_b64":"Szo30q7HEYqnP4bg78X8wh4YRG1lxAedGkZUWxWZm7Mxbl/9f5snnFn6xL+TKLn70sPTlfSETG5ofce6BImfDw==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T01:43:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GrlRvCBoboWLkqgAAm8H+ULeFhtygqHxAWfqEDp4R/rv2rGtmvXmrKG9KjE59crUVUDJ2On2/xat4FM2v/4PBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.916856Z"},"content_sha256":"db803249f12ba6ecc6ca57fbb7b801729ab69bc688918c8fbaeb81333cd543c9","schema_version":"1.0","event_id":"sha256:db803249f12ba6ecc6ca57fbb7b801729ab69bc688918c8fbaeb81333cd543c9"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","target":"integrity","payload":{"note":"Identifier '10.1177/02783649134912973' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Geiger, A., Lenz, P., Stiller, C., Urtasun, R.: Vision meets robotics: The KITTI dataset. International Journal of Robotics Research32(11), 1231–1237 (2013). https://doi.org/10.1177/02783649134912973, 4, 5","arxiv_id":"2607.08771","detector":"doi_compliance","evidence":{"doi":"10.1177/02783649134912973","arxiv_id":null,"ref_index":24,"raw_excerpt":"Geiger, A., Lenz, P., Stiller, C., Urtasun, R.: Vision meets robotics: The KITTI dataset. International Journal of Robotics Research32(11), 1231–1237 (2013). https://doi.org/10.1177/02783649134912973, 4, 5","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"]},"severity":"critical","ref_index":24,"audited_at":"2026-07-10T01:41:31.321281Z","event_type":"pith.integrity.v1","detected_doi":"10.1177/02783649134912973","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"67b0ab77d7b5fb0c34398b42a09bf8c6803d74013937957bde9274c3f6de3819","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":11734,"payload_sha256":"a3bdafc84a56d3243aaa5e4088e0ca294e5ffa368e64aad1ed721634e8def87e","signature_b64":"qkoCE4I4TXezcknZbrf+B+oaBR505Pbi798nqTPKWSPEVXt+exOSNW73iZw4qgDfOTBbgmvz0xk/cM4yUknMBg==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-10T01:43:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"03km0BbNVwTTz9jJSXL4d3gxcADH0rQmiIDI8jPAWeeTzCnNt7RI9fegHnbaw8C9IGvYX61Of8tBvWGCs8uECg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T15:53:50.917130Z"},"content_sha256":"98ac5b865e17a30afed8b9f93a1ed9268fa5c308026dcb054802f744e43ab6b6","schema_version":"1.0","event_id":"sha256:98ac5b865e17a30afed8b9f93a1ed9268fa5c308026dcb054802f744e43ab6b6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZNPBJ5MSL644RCKCTPAQRMSPSG/bundle.json","state_url":"https://pith.science/pith/ZNPBJ5MSL644RCKCTPAQRMSPSG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZNPBJ5MSL644RCKCTPAQRMSPSG/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-11T15:53:50Z","links":{"resolver":"https://pith.science/pith/ZNPBJ5MSL644RCKCTPAQRMSPSG","bundle":"https://pith.science/pith/ZNPBJ5MSL644RCKCTPAQRMSPSG/bundle.json","state":"https://pith.science/pith/ZNPBJ5MSL644RCKCTPAQRMSPSG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZNPBJ5MSL644RCKCTPAQRMSPSG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ZNPBJ5MSL644RCKCTPAQRMSPSG","merge_version":"pith-open-graph-merge-v1","event_count":9,"valid_event_count":9,"invalid_event_count":0,"equivocation_count":1,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"c2df81c4c899bd31880e05872a523653398f8582ee14ac773af152fad155b89c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-09T17:59:58Z","title_canon_sha256":"913cc9bb32a8a59a036aab62f79a948520233817f091c2c09ec7612955ad302d"},"schema_version":"1.0","source":{"id":"2607.08771","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.08771","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"arxiv_version","alias_value":"2607.08771v1","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.08771","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"pith_short_12","alias_value":"ZNPBJ5MSL644","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZNPBJ5MSL644RCKC","created_at":"2026-07-10T01:19:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZNPBJ5MS","created_at":"2026-07-10T01:19:59Z"}],"graph_snapshots":[{"event_id":"sha256:6ce59600e71f5d532864135249c02a398c0ed3e563de0342b14de27cfd76a93f","target":"graph","created_at":"2026-07-10T01:19:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2607.08771/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Monocular depth estimation has seen remarkable progress through foundation models achieving robust zero-shot generalization, yet their computational demands place them far beyond the reach of embedded and mobile platforms. Lightweight alternatives exist, but have been developed almost exclusively within single-domain, self-supervised paradigms, failing silently under domain shift. We present ZipDepth, a compact monocular depth network that bridges this gap by combining an efficient reparameterizable encoder-decoder with large-scale knowledge distillation from a foundation model over a large mu","authors_text":"Fabio Tosi, Luca Bartolomei, Matteo Poggi, Stefano Mattoccia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-09T17:59:58Z","title":"ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.08771","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:59e2d735b86f0917b4c8003c0233ac8ca10da65beee85a3547ce61453511996f","target":"record","created_at":"2026-07-10T01:19:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"c2df81c4c899bd31880e05872a523653398f8582ee14ac773af152fad155b89c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-09T17:59:58Z","title_canon_sha256":"913cc9bb32a8a59a036aab62f79a948520233817f091c2c09ec7612955ad302d"},"schema_version":"1.0","source":{"id":"2607.08771","kind":"arxiv","version":1}},"canonical_sha256":"cb5e14f5925fb9c889429bc108b24f91bcd41c0f12f3a3f4d781118a0c74c0d4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb5e14f5925fb9c889429bc108b24f91bcd41c0f12f3a3f4d781118a0c74c0d4","first_computed_at":"2026-07-10T01:19:59.865084Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-10T01:19:59.865084Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"guiKB6HUmoRPsbUSOCA/20iAOnp2WME1jfZWzYxk4UfORcrZY5RA5GCdnULKvX2eiM4/sQ9GIOxIVtSwLO1oBw==","signature_status":"signed_v1","signed_at":"2026-07-10T01:19:59.865508Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.08771","source_kind":"arxiv","source_version":1}}},"equivocations":[{"signer_id":"pith.science","event_type":"integrity_finding","target":"integrity","event_ids":["sha256:96ff387ec1f47ca0841a7cd68c02838e4af660b4d9c7c0cccbb6b1328a677b6b","sha256:98ac5b865e17a30afed8b9f93a1ed9268fa5c308026dcb054802f744e43ab6b6","sha256:9adcd4793078689da7ed13cbdea1fb1e24a2f9ae047f0f03daff7287fc6224e7","sha256:db803249f12ba6ecc6ca57fbb7b801729ab69bc688918c8fbaeb81333cd543c9","sha256:e8b22b9441c30900adce806e75039877f81c11c5d042bf71d3d056ef029659bb","sha256:f2d0af0a6db5a4982448f7f76e7855f66e0f5436abf45f734e0da9a04ca4ce64","sha256:f4d0a6a8ff036495ab68610aaa079f32201c3c5f704b3551d1b1c6a1dfc0d2a5"]}],"invalid_events":[],"applied_event_ids":["sha256:59e2d735b86f0917b4c8003c0233ac8ca10da65beee85a3547ce61453511996f","sha256:6ce59600e71f5d532864135249c02a398c0ed3e563de0342b14de27cfd76a93f"],"state_sha256":"5e49a71a4e57a3f15e35f0ffb6915f1b67b7ba820ae78107b7f5684c7947fa78"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fG2yGJhV1Qs89EDtf5lOupAWk6HBUeYJYQdxA/EkS/l4NPUcafckwm0ky3bC8PxgXeFuQFrk1jXmtL+CnLOjBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T15:53:50.919707Z","bundle_sha256":"60fb0640d0390f385cc678eafdfc71b05d8a7fd08f93f1a6d5573c5fff457eef"}}