{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:RSTZWMLTXXS75JFHSZTGK3MPWL","short_pith_number":"pith:RSTZWMLT","canonical_record":{"source":{"id":"1912.03426","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-07T03:44:28Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"07b6f2768de8bf4af55dfd82f0ebbd91a03796f8321673d4e275408a855a617b","abstract_canon_sha256":"55ae93748f0cd6a8c9ac7c41365dedbb20dfc4b577daf4c7669f57af6fa6b74e"},"schema_version":"1.0"},"canonical_sha256":"8ca79b3173bde5fea4a79666656d8fb2d09d47105ccfed6be51d5242986ed8ed","source":{"kind":"arxiv","id":"1912.03426","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.03426","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"arxiv_version","alias_value":"1912.03426v3","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.03426","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"pith_short_12","alias_value":"RSTZWMLTXXS7","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"pith_short_16","alias_value":"RSTZWMLTXXS75JFH","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"pith_short_8","alias_value":"RSTZWMLT","created_at":"2026-07-05T01:52:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:RSTZWMLTXXS75JFHSZTGK3MPWL","target":"record","payload":{"canonical_record":{"source":{"id":"1912.03426","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-07T03:44:28Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"07b6f2768de8bf4af55dfd82f0ebbd91a03796f8321673d4e275408a855a617b","abstract_canon_sha256":"55ae93748f0cd6a8c9ac7c41365dedbb20dfc4b577daf4c7669f57af6fa6b74e"},"schema_version":"1.0"},"canonical_sha256":"8ca79b3173bde5fea4a79666656d8fb2d09d47105ccfed6be51d5242986ed8ed","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:52:33.900073Z","signature_b64":"8tKjkTahJc6hWT6is1GquT+28Y2XpnP1kkNX2XrSdkWZttS7ce90ONqJ7XtmXWyQBHOuU2GGPugB6cYSox+vBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8ca79b3173bde5fea4a79666656d8fb2d09d47105ccfed6be51d5242986ed8ed","last_reissued_at":"2026-07-05T01:52:33.899600Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:52:33.899600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.03426","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:52:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XS8ear5ZYJ4lTCyEB4p+REysMoxAWi1IzePEyI4h96tWwttCt/QTDrklDLqujLyzHsskPgUC4GxrCd73sgUxDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:29:54.485212Z"},"content_sha256":"e38d8d7f63deedcc6bb7f73b7f0998c07eab479ee7269d33ac90dba439c517ba","schema_version":"1.0","event_id":"sha256:e38d8d7f63deedcc6bb7f73b7f0998c07eab479ee7269d33ac90dba439c517ba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:RSTZWMLTXXS75JFHSZTGK3MPWL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Self-Supervised 3D Keypoint Learning for Ego-motion Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.RO"],"primary_cat":"cs.CV","authors_text":"Adrien Gaidon, Hanme Kim, Jiexiong Tang, Patric Jensfelt, Rares Ambrus, Sudeep Pillai, Vitor Guizilini","submitted_at":"2019-12-07T03:44:28Z","abstract_excerpt":"Detecting and matching robust viewpoint-invariant keypoints is critical for visual SLAM and Structure-from-Motion. State-of-the-art learning-based methods generate training samples via homography adaptation to create 2D synthetic views with known keypoint matches from a single image. This approach, however, does not generalize to non-planar 3D scenes with illumination variations commonly seen in real-world videos. In this work, we propose self-supervised learning of depth-aware keypoints directly from unlabeled videos. We jointly learn keypoint and depth estimation networks by combining appear"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.03426","kind":"arxiv","version":3},"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/1912.03426/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":"2026-07-05T01:52:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dj2BqalQSIwhbHclyetxqRNT9cqFVItkXA8UTpBTnkVPLKMW946D5qXrK3S2zTJmYXt9L8x1W/A+8BLhy/BRCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:29:54.485773Z"},"content_sha256":"9339277ac3a158b45af9c63792567c816ed122714b8ae5083ce4d9e4dee55c33","schema_version":"1.0","event_id":"sha256:9339277ac3a158b45af9c63792567c816ed122714b8ae5083ce4d9e4dee55c33"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RSTZWMLTXXS75JFHSZTGK3MPWL/bundle.json","state_url":"https://pith.science/pith/RSTZWMLTXXS75JFHSZTGK3MPWL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RSTZWMLTXXS75JFHSZTGK3MPWL/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":"2026-08-04T21:29:54Z","links":{"resolver":"https://pith.science/pith/RSTZWMLTXXS75JFHSZTGK3MPWL","bundle":"https://pith.science/pith/RSTZWMLTXXS75JFHSZTGK3MPWL/bundle.json","state":"https://pith.science/pith/RSTZWMLTXXS75JFHSZTGK3MPWL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RSTZWMLTXXS75JFHSZTGK3MPWL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:RSTZWMLTXXS75JFHSZTGK3MPWL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"55ae93748f0cd6a8c9ac7c41365dedbb20dfc4b577daf4c7669f57af6fa6b74e","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-07T03:44:28Z","title_canon_sha256":"07b6f2768de8bf4af55dfd82f0ebbd91a03796f8321673d4e275408a855a617b"},"schema_version":"1.0","source":{"id":"1912.03426","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.03426","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"arxiv_version","alias_value":"1912.03426v3","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.03426","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"pith_short_12","alias_value":"RSTZWMLTXXS7","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"pith_short_16","alias_value":"RSTZWMLTXXS75JFH","created_at":"2026-07-05T01:52:33Z"},{"alias_kind":"pith_short_8","alias_value":"RSTZWMLT","created_at":"2026-07-05T01:52:33Z"}],"graph_snapshots":[{"event_id":"sha256:9339277ac3a158b45af9c63792567c816ed122714b8ae5083ce4d9e4dee55c33","target":"graph","created_at":"2026-07-05T01:52:33Z","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/1912.03426/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Detecting and matching robust viewpoint-invariant keypoints is critical for visual SLAM and Structure-from-Motion. State-of-the-art learning-based methods generate training samples via homography adaptation to create 2D synthetic views with known keypoint matches from a single image. This approach, however, does not generalize to non-planar 3D scenes with illumination variations commonly seen in real-world videos. In this work, we propose self-supervised learning of depth-aware keypoints directly from unlabeled videos. We jointly learn keypoint and depth estimation networks by combining appear","authors_text":"Adrien Gaidon, Hanme Kim, Jiexiong Tang, Patric Jensfelt, Rares Ambrus, Sudeep Pillai, Vitor Guizilini","cross_cats":["cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-07T03:44:28Z","title":"Self-Supervised 3D Keypoint Learning for Ego-motion Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.03426","kind":"arxiv","version":3},"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:e38d8d7f63deedcc6bb7f73b7f0998c07eab479ee7269d33ac90dba439c517ba","target":"record","created_at":"2026-07-05T01:52:33Z","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":"55ae93748f0cd6a8c9ac7c41365dedbb20dfc4b577daf4c7669f57af6fa6b74e","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-07T03:44:28Z","title_canon_sha256":"07b6f2768de8bf4af55dfd82f0ebbd91a03796f8321673d4e275408a855a617b"},"schema_version":"1.0","source":{"id":"1912.03426","kind":"arxiv","version":3}},"canonical_sha256":"8ca79b3173bde5fea4a79666656d8fb2d09d47105ccfed6be51d5242986ed8ed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8ca79b3173bde5fea4a79666656d8fb2d09d47105ccfed6be51d5242986ed8ed","first_computed_at":"2026-07-05T01:52:33.899600Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:52:33.899600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8tKjkTahJc6hWT6is1GquT+28Y2XpnP1kkNX2XrSdkWZttS7ce90ONqJ7XtmXWyQBHOuU2GGPugB6cYSox+vBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:52:33.900073Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.03426","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e38d8d7f63deedcc6bb7f73b7f0998c07eab479ee7269d33ac90dba439c517ba","sha256:9339277ac3a158b45af9c63792567c816ed122714b8ae5083ce4d9e4dee55c33"],"state_sha256":"db0164d8ae87073f12da0eefd144c3de790c199eea9530b0b63566642bcc6985"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q5UVqklf09QAL3UDuGFoDH/GXBounXTU6ZcpJ8hxhc4ZC80JqWVX1vONkItjurYhowzpsAnQYZyi3S/BQ9S2Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T21:29:54.491403Z","bundle_sha256":"77162eb0113224a2fec2796ccaefb68f3dd99d3e8289575a51156f6ce4f3ea05"}}