{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:KE5KXT3QAOMI5ABVZBOKQLA34P","short_pith_number":"pith:KE5KXT3Q","canonical_record":{"source":{"id":"2011.04123","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-09T01:03:13Z","cross_cats_sorted":[],"title_canon_sha256":"7d11cdf41d1ca782099e67e3f2d54634738bef5175a7b1f7811e0bce86e7a5b8","abstract_canon_sha256":"2aa6734947382efc16d0103983483dfa29ae5c34d640c5a0c4705ea3c34a65cb"},"schema_version":"1.0"},"canonical_sha256":"513aabcf7003988e8035c85ca82c1be3c6239b4c264c7a93db7e2192dd69aec5","source":{"kind":"arxiv","id":"2011.04123","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.04123","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"arxiv_version","alias_value":"2011.04123v1","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.04123","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"pith_short_12","alias_value":"KE5KXT3QAOMI","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"pith_short_16","alias_value":"KE5KXT3QAOMI5ABV","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"pith_short_8","alias_value":"KE5KXT3Q","created_at":"2026-07-05T01:50:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:KE5KXT3QAOMI5ABVZBOKQLA34P","target":"record","payload":{"canonical_record":{"source":{"id":"2011.04123","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-09T01:03:13Z","cross_cats_sorted":[],"title_canon_sha256":"7d11cdf41d1ca782099e67e3f2d54634738bef5175a7b1f7811e0bce86e7a5b8","abstract_canon_sha256":"2aa6734947382efc16d0103983483dfa29ae5c34d640c5a0c4705ea3c34a65cb"},"schema_version":"1.0"},"canonical_sha256":"513aabcf7003988e8035c85ca82c1be3c6239b4c264c7a93db7e2192dd69aec5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:50:02.602529Z","signature_b64":"oW+2cysAK0ZI6KMVqtSyKgOgxN7wu9fGZqewj4EK4D7y3x6lTlaTm7KWtcVW0LEdc4spX8baOqQyQMbc5TTYBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"513aabcf7003988e8035c85ca82c1be3c6239b4c264c7a93db7e2192dd69aec5","last_reissued_at":"2026-07-05T01:50:02.602191Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:50:02.602191Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.04123","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":"2026-07-05T01:50:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cmgxYZu0LtMV5pwL6NLbK74J/gfQFcunKOsLPWhrsaJHyZDb7PoV33BHB1bRSfUXNJXBhvV7+1DeSCN4POhCBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T09:19:45.278931Z"},"content_sha256":"87b45816e53f0fd811f9b3ab4fb3d053850c4226165375f1c717d73ecd928a28","schema_version":"1.0","event_id":"sha256:87b45816e53f0fd811f9b3ab4fb3d053850c4226165375f1c717d73ecd928a28"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:KE5KXT3QAOMI5ABVZBOKQLA34P","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guoping Qiu, Jiasong Zhu, Jun Liu, Qing Li, Qingquan Li, Rui Cao, Sen Jia","submitted_at":"2020-11-09T01:03:13Z","abstract_excerpt":"Estimating depth from RGB images can facilitate many computer vision tasks, such as indoor localization, height estimation, and simultaneous localization and mapping (SLAM). Recently, monocular depth estimation has obtained great progress owing to the rapid development of deep learning techniques. They surpass traditional machine learning-based methods by a large margin in terms of accuracy and speed. Despite the rapid progress in this topic, there are lacking of a comprehensive review, which is needed to summarize the current progress and provide the future directions. In this survey, we firs"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.04123","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/2011.04123/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":"2026-07-05T01:50:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6V3UIdvDC/QcgXNAJIKclZdbUD10XWeUd9yefhlqKN25yRYvIZDTwal11qCoIeM1Nfb3Rl1MQP7zMOHSZ4avAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T09:19:45.279355Z"},"content_sha256":"98e76aec62119da2178589f7948083bfc4e12058f00d43313beb45a8444146b8","schema_version":"1.0","event_id":"sha256:98e76aec62119da2178589f7948083bfc4e12058f00d43313beb45a8444146b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KE5KXT3QAOMI5ABVZBOKQLA34P/bundle.json","state_url":"https://pith.science/pith/KE5KXT3QAOMI5ABVZBOKQLA34P/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KE5KXT3QAOMI5ABVZBOKQLA34P/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":"2026-07-07T09:19:45Z","links":{"resolver":"https://pith.science/pith/KE5KXT3QAOMI5ABVZBOKQLA34P","bundle":"https://pith.science/pith/KE5KXT3QAOMI5ABVZBOKQLA34P/bundle.json","state":"https://pith.science/pith/KE5KXT3QAOMI5ABVZBOKQLA34P/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KE5KXT3QAOMI5ABVZBOKQLA34P/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:KE5KXT3QAOMI5ABVZBOKQLA34P","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":"2aa6734947382efc16d0103983483dfa29ae5c34d640c5a0c4705ea3c34a65cb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-09T01:03:13Z","title_canon_sha256":"7d11cdf41d1ca782099e67e3f2d54634738bef5175a7b1f7811e0bce86e7a5b8"},"schema_version":"1.0","source":{"id":"2011.04123","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.04123","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"arxiv_version","alias_value":"2011.04123v1","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.04123","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"pith_short_12","alias_value":"KE5KXT3QAOMI","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"pith_short_16","alias_value":"KE5KXT3QAOMI5ABV","created_at":"2026-07-05T01:50:02Z"},{"alias_kind":"pith_short_8","alias_value":"KE5KXT3Q","created_at":"2026-07-05T01:50:02Z"}],"graph_snapshots":[{"event_id":"sha256:98e76aec62119da2178589f7948083bfc4e12058f00d43313beb45a8444146b8","target":"graph","created_at":"2026-07-05T01:50:02Z","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/2011.04123/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Estimating depth from RGB images can facilitate many computer vision tasks, such as indoor localization, height estimation, and simultaneous localization and mapping (SLAM). Recently, monocular depth estimation has obtained great progress owing to the rapid development of deep learning techniques. They surpass traditional machine learning-based methods by a large margin in terms of accuracy and speed. Despite the rapid progress in this topic, there are lacking of a comprehensive review, which is needed to summarize the current progress and provide the future directions. In this survey, we firs","authors_text":"Guoping Qiu, Jiasong Zhu, Jun Liu, Qing Li, Qingquan Li, Rui Cao, Sen Jia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-09T01:03:13Z","title":"Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.04123","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":"sha256:87b45816e53f0fd811f9b3ab4fb3d053850c4226165375f1c717d73ecd928a28","target":"record","created_at":"2026-07-05T01:50:02Z","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":"2aa6734947382efc16d0103983483dfa29ae5c34d640c5a0c4705ea3c34a65cb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-09T01:03:13Z","title_canon_sha256":"7d11cdf41d1ca782099e67e3f2d54634738bef5175a7b1f7811e0bce86e7a5b8"},"schema_version":"1.0","source":{"id":"2011.04123","kind":"arxiv","version":1}},"canonical_sha256":"513aabcf7003988e8035c85ca82c1be3c6239b4c264c7a93db7e2192dd69aec5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"513aabcf7003988e8035c85ca82c1be3c6239b4c264c7a93db7e2192dd69aec5","first_computed_at":"2026-07-05T01:50:02.602191Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:50:02.602191Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oW+2cysAK0ZI6KMVqtSyKgOgxN7wu9fGZqewj4EK4D7y3x6lTlaTm7KWtcVW0LEdc4spX8baOqQyQMbc5TTYBg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:50:02.602529Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.04123","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:87b45816e53f0fd811f9b3ab4fb3d053850c4226165375f1c717d73ecd928a28","sha256:98e76aec62119da2178589f7948083bfc4e12058f00d43313beb45a8444146b8"],"state_sha256":"511778eb426ca260825483a71fd145c9e544938af78ac0f3af21c9b7f8b32795"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hBBI3XKANXXbdLwF9d3r05wfxg8mzs4M9428Zsu62zL8TwWZsMA/PPp2nv4DztRyW0dnN1wYxQV2zVsDiNxDDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T09:19:45.281275Z","bundle_sha256":"b43ab951b1e1af28484c5436037747b33cfd11e4c68c1c2c9c459a776c9e26ef"}}