{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ZVORQA2SFFSHYKKJUS2TRVH4QX","short_pith_number":"pith:ZVORQA2S","canonical_record":{"source":{"id":"2004.04345","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-09T03:12:52Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"087726d31d7863aa5734f799850a3d48ab3d6a6d3f534e004e7f405ff00976e0","abstract_canon_sha256":"0bd3fa61769f9f218f6c9af076217741ac69b2b3ee874caf0f641ceaba2623a0"},"schema_version":"1.0"},"canonical_sha256":"cd5d18035229647c2949a4b538d4fc85cda350aafab22e514d6896604f18377e","source":{"kind":"arxiv","id":"2004.04345","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.04345","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"arxiv_version","alias_value":"2004.04345v3","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.04345","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_12","alias_value":"ZVORQA2SFFSH","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_16","alias_value":"ZVORQA2SFFSHYKKJ","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_8","alias_value":"ZVORQA2S","created_at":"2026-07-05T02:31:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ZVORQA2SFFSHYKKJUS2TRVH4QX","target":"record","payload":{"canonical_record":{"source":{"id":"2004.04345","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-09T03:12:52Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"087726d31d7863aa5734f799850a3d48ab3d6a6d3f534e004e7f405ff00976e0","abstract_canon_sha256":"0bd3fa61769f9f218f6c9af076217741ac69b2b3ee874caf0f641ceaba2623a0"},"schema_version":"1.0"},"canonical_sha256":"cd5d18035229647c2949a4b538d4fc85cda350aafab22e514d6896604f18377e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:31:17.723459Z","signature_b64":"Oh4mi7IzUSi7AXKwJXUCO1Gc61ftGJEPUoNXGMLEudZ1qrys8KR9ffPiDAfpO9N7Y6qGZkP6eDtrDbVtfW1KCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd5d18035229647c2949a4b538d4fc85cda350aafab22e514d6896604f18377e","last_reissued_at":"2026-07-05T02:31:17.723022Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:31:17.723022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.04345","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":"2026-07-05T02:31:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7+VSKKOlzkJqzthWPQZ8LCWd/kzPpYbYaUvGEEZIPHOwvkCjwPeU8l8BCnh5GynluVlMr+XvbM3Tm9RsL0X7Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T01:08:40.230011Z"},"content_sha256":"50726e334b3dd7a07ef13e57f38b3d23d566472fcacf1fdd6ef657ca15c186ca","schema_version":"1.0","event_id":"sha256:50726e334b3dd7a07ef13e57f38b3d23d566472fcacf1fdd6ef657ca15c186ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ZVORQA2SFFSHYKKJUS2TRVH4QX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Masked GANs for Unsupervised Depth and Pose Prediction with Scale Consistency","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Chaoqiang Zhao, Chongzhen Zhang, Gary G. Yen, Qiyu Sun, Yang Tang","submitted_at":"2020-04-09T03:12:52Z","abstract_excerpt":"Previous work has shown that adversarial learning can be used for unsupervised monocular depth and visual odometry (VO) estimation, in which the adversarial loss and the geometric image reconstruction loss are utilized as the mainly supervisory signals to train the whole unsupervised framework. However, the performance of the adversarial framework and image reconstruction is usually limited by occlusions and the visual field changes between frames. This paper proposes a masked generative adversarial network (GAN) for unsupervised monocular depth and ego-motion estimation.The MaskNet and Boolea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.04345","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/2004.04345/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":"2026-07-05T02:31:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ruut9Kh8PpTqdE9S80gjXmxTgAYkokIkBY/yzO6xGW1ZbQyDNbkVmyb1ooXxITFID08aeW2/+eYgGvoqOHPiBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T01:08:40.230387Z"},"content_sha256":"6a7575a426035eb62e5a7111a75a7f3485a99f5606ba0e87f9bb8eebc21d0ef1","schema_version":"1.0","event_id":"sha256:6a7575a426035eb62e5a7111a75a7f3485a99f5606ba0e87f9bb8eebc21d0ef1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZVORQA2SFFSHYKKJUS2TRVH4QX/bundle.json","state_url":"https://pith.science/pith/ZVORQA2SFFSHYKKJUS2TRVH4QX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZVORQA2SFFSHYKKJUS2TRVH4QX/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":"2026-07-27T01:08:40Z","links":{"resolver":"https://pith.science/pith/ZVORQA2SFFSHYKKJUS2TRVH4QX","bundle":"https://pith.science/pith/ZVORQA2SFFSHYKKJUS2TRVH4QX/bundle.json","state":"https://pith.science/pith/ZVORQA2SFFSHYKKJUS2TRVH4QX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZVORQA2SFFSHYKKJUS2TRVH4QX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ZVORQA2SFFSHYKKJUS2TRVH4QX","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":"0bd3fa61769f9f218f6c9af076217741ac69b2b3ee874caf0f641ceaba2623a0","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-09T03:12:52Z","title_canon_sha256":"087726d31d7863aa5734f799850a3d48ab3d6a6d3f534e004e7f405ff00976e0"},"schema_version":"1.0","source":{"id":"2004.04345","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.04345","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"arxiv_version","alias_value":"2004.04345v3","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.04345","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_12","alias_value":"ZVORQA2SFFSH","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_16","alias_value":"ZVORQA2SFFSHYKKJ","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_8","alias_value":"ZVORQA2S","created_at":"2026-07-05T02:31:17Z"}],"graph_snapshots":[{"event_id":"sha256:6a7575a426035eb62e5a7111a75a7f3485a99f5606ba0e87f9bb8eebc21d0ef1","target":"graph","created_at":"2026-07-05T02:31:17Z","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/2004.04345/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Previous work has shown that adversarial learning can be used for unsupervised monocular depth and visual odometry (VO) estimation, in which the adversarial loss and the geometric image reconstruction loss are utilized as the mainly supervisory signals to train the whole unsupervised framework. However, the performance of the adversarial framework and image reconstruction is usually limited by occlusions and the visual field changes between frames. This paper proposes a masked generative adversarial network (GAN) for unsupervised monocular depth and ego-motion estimation.The MaskNet and Boolea","authors_text":"Chaoqiang Zhao, Chongzhen Zhang, Gary G. Yen, Qiyu Sun, Yang Tang","cross_cats":["eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-09T03:12:52Z","title":"Masked GANs for Unsupervised Depth and Pose Prediction with Scale Consistency"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.04345","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":"sha256:50726e334b3dd7a07ef13e57f38b3d23d566472fcacf1fdd6ef657ca15c186ca","target":"record","created_at":"2026-07-05T02:31:17Z","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":"0bd3fa61769f9f218f6c9af076217741ac69b2b3ee874caf0f641ceaba2623a0","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-09T03:12:52Z","title_canon_sha256":"087726d31d7863aa5734f799850a3d48ab3d6a6d3f534e004e7f405ff00976e0"},"schema_version":"1.0","source":{"id":"2004.04345","kind":"arxiv","version":3}},"canonical_sha256":"cd5d18035229647c2949a4b538d4fc85cda350aafab22e514d6896604f18377e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cd5d18035229647c2949a4b538d4fc85cda350aafab22e514d6896604f18377e","first_computed_at":"2026-07-05T02:31:17.723022Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:31:17.723022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Oh4mi7IzUSi7AXKwJXUCO1Gc61ftGJEPUoNXGMLEudZ1qrys8KR9ffPiDAfpO9N7Y6qGZkP6eDtrDbVtfW1KCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:31:17.723459Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.04345","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:50726e334b3dd7a07ef13e57f38b3d23d566472fcacf1fdd6ef657ca15c186ca","sha256:6a7575a426035eb62e5a7111a75a7f3485a99f5606ba0e87f9bb8eebc21d0ef1"],"state_sha256":"3d74d8b45e00686ef0126c54098a14ac129a471b2865b6a55655ad5371dbe6e5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GVUOeO+ThSuqujM6Ox0hpPGIVDBFlwCpvEz51hskjy8WA/35Cu4SsDWGYlp9fZp9nZSFA+ET1Y9ou00tzbs/BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-27T01:08:40.232814Z","bundle_sha256":"00d7eb71172336010f0eccc28fd3f328ad3e49990ee726d14e34bca7e738d132"}}