{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:QZH2T32RY4K6Z4JJYA4P5RWDGX","short_pith_number":"pith:QZH2T32R","canonical_record":{"source":{"id":"1907.06023","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-13T07:31:24Z","cross_cats_sorted":[],"title_canon_sha256":"f1b51cdd8740eb760d61242cb4b455424d8c9ad1b81f50c42d04c74a1e42a0c2","abstract_canon_sha256":"a6e123ccfd478880c8d3ea5dd848b3c1259432542d1b343adf3f90ce9f485011"},"schema_version":"1.0"},"canonical_sha256":"864fa9ef51c715ecf129c038fec6c335d36713a63e1563732b79792b8fdb3bb1","source":{"kind":"arxiv","id":"1907.06023","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.06023","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"arxiv_version","alias_value":"1907.06023v1","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.06023","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"pith_short_12","alias_value":"QZH2T32RY4K6","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"QZH2T32RY4K6Z4JJ","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"QZH2T32R","created_at":"2026-05-18T12:33:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:QZH2T32RY4K6Z4JJYA4P5RWDGX","target":"record","payload":{"canonical_record":{"source":{"id":"1907.06023","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-13T07:31:24Z","cross_cats_sorted":[],"title_canon_sha256":"f1b51cdd8740eb760d61242cb4b455424d8c9ad1b81f50c42d04c74a1e42a0c2","abstract_canon_sha256":"a6e123ccfd478880c8d3ea5dd848b3c1259432542d1b343adf3f90ce9f485011"},"schema_version":"1.0"},"canonical_sha256":"864fa9ef51c715ecf129c038fec6c335d36713a63e1563732b79792b8fdb3bb1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:42.652254Z","signature_b64":"QOFXeIyYiwOw+bPWCJfMVuyGwMHNFQ/vv8c2AW6hYjdpId8P3CCKlDjgbUtDR32YbXUKcenPI6PLXb8YqJGcBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"864fa9ef51c715ecf129c038fec6c335d36713a63e1563732b79792b8fdb3bb1","last_reissued_at":"2026-05-17T23:40:42.651603Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:42.651603Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.06023","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":"2026-05-17T23:40:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uzRHL+46ua1TDDmM/IoSoyFFVwNJVUBM149PjEb4EDomElMzcyuB6th7kujTBdwrYxha1Y1xaYgUdnpPelA9AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T05:25:26.562616Z"},"content_sha256":"7305abe074f82f0bad9f5977954cbd728931a5d9d24bd620d2917c55803c4654","schema_version":"1.0","event_id":"sha256:7305abe074f82f0bad9f5977954cbd728931a5d9d24bd620d2917c55803c4654"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:QZH2T32RY4K6Z4JJYA4P5RWDGX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Structure-Aware Residual Pyramid Network for Monocular Depth Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Xiaotian Chen, Xuejin Chen, Zheng-Jun Zha","submitted_at":"2019-07-13T07:31:24Z","abstract_excerpt":"Monocular depth estimation is an essential task for scene understanding. The underlying structure of objects and stuff in a complex scene is critical to recovering accurate and visually-pleasing depth maps. Global structure conveys scene layouts, while local structure reflects shape details. Recently developed approaches based on convolutional neural networks (CNNs) significantly improve the performance of depth estimation. However, few of them take into account multi-scale structures in complex scenes. In this paper, we propose a Structure-Aware Residual Pyramid Network (SARPN) to exploit mul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.06023","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":""},"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":"2026-05-17T23:40:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1vpnsUB6KHe9zVtsbTZTJcLhC7HcJ2j2DtjcvlSS7qFy0FXXXS11QBYORNTO/O6sHVVNkCcZeYTubQnpk/iRBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T05:25:26.562993Z"},"content_sha256":"78a40367c53907ea321ed4a541d5f11ca9205acbf0de6446365317bdff118437","schema_version":"1.0","event_id":"sha256:78a40367c53907ea321ed4a541d5f11ca9205acbf0de6446365317bdff118437"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QZH2T32RY4K6Z4JJYA4P5RWDGX/bundle.json","state_url":"https://pith.science/pith/QZH2T32RY4K6Z4JJYA4P5RWDGX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QZH2T32RY4K6Z4JJYA4P5RWDGX/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":"2026-05-23T05:25:26Z","links":{"resolver":"https://pith.science/pith/QZH2T32RY4K6Z4JJYA4P5RWDGX","bundle":"https://pith.science/pith/QZH2T32RY4K6Z4JJYA4P5RWDGX/bundle.json","state":"https://pith.science/pith/QZH2T32RY4K6Z4JJYA4P5RWDGX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QZH2T32RY4K6Z4JJYA4P5RWDGX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:QZH2T32RY4K6Z4JJYA4P5RWDGX","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":"a6e123ccfd478880c8d3ea5dd848b3c1259432542d1b343adf3f90ce9f485011","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-13T07:31:24Z","title_canon_sha256":"f1b51cdd8740eb760d61242cb4b455424d8c9ad1b81f50c42d04c74a1e42a0c2"},"schema_version":"1.0","source":{"id":"1907.06023","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.06023","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"arxiv_version","alias_value":"1907.06023v1","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.06023","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"pith_short_12","alias_value":"QZH2T32RY4K6","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"QZH2T32RY4K6Z4JJ","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"QZH2T32R","created_at":"2026-05-18T12:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:78a40367c53907ea321ed4a541d5f11ca9205acbf0de6446365317bdff118437","target":"graph","created_at":"2026-05-17T23:40:42Z","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"},"paper":{"abstract_excerpt":"Monocular depth estimation is an essential task for scene understanding. The underlying structure of objects and stuff in a complex scene is critical to recovering accurate and visually-pleasing depth maps. Global structure conveys scene layouts, while local structure reflects shape details. Recently developed approaches based on convolutional neural networks (CNNs) significantly improve the performance of depth estimation. However, few of them take into account multi-scale structures in complex scenes. In this paper, we propose a Structure-Aware Residual Pyramid Network (SARPN) to exploit mul","authors_text":"Xiaotian Chen, Xuejin Chen, Zheng-Jun Zha","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-13T07:31:24Z","title":"Structure-Aware Residual Pyramid Network for Monocular Depth Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.06023","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":"sha256:7305abe074f82f0bad9f5977954cbd728931a5d9d24bd620d2917c55803c4654","target":"record","created_at":"2026-05-17T23:40:42Z","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":"a6e123ccfd478880c8d3ea5dd848b3c1259432542d1b343adf3f90ce9f485011","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-13T07:31:24Z","title_canon_sha256":"f1b51cdd8740eb760d61242cb4b455424d8c9ad1b81f50c42d04c74a1e42a0c2"},"schema_version":"1.0","source":{"id":"1907.06023","kind":"arxiv","version":1}},"canonical_sha256":"864fa9ef51c715ecf129c038fec6c335d36713a63e1563732b79792b8fdb3bb1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"864fa9ef51c715ecf129c038fec6c335d36713a63e1563732b79792b8fdb3bb1","first_computed_at":"2026-05-17T23:40:42.651603Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:42.651603Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QOFXeIyYiwOw+bPWCJfMVuyGwMHNFQ/vv8c2AW6hYjdpId8P3CCKlDjgbUtDR32YbXUKcenPI6PLXb8YqJGcBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:42.652254Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.06023","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7305abe074f82f0bad9f5977954cbd728931a5d9d24bd620d2917c55803c4654","sha256:78a40367c53907ea321ed4a541d5f11ca9205acbf0de6446365317bdff118437"],"state_sha256":"6873a38c8ef42bf90b50803b5e88ab4c2b0b7fc1ff6edc69377d068092132732"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s2aquQH0BFW1/+NNtPWxlSg6M1iUvR2S+Z+Oyf30b96ubQmmLs9mhxdB475h7M3XKC0tup2bT40T3te6DbWbAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T05:25:26.565560Z","bundle_sha256":"f0c693af9e4b5008624fb47f022470a3550537b91f7dfba5c5aca96a8ae2e405"}}