{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:MJAMBL5D7X37JEMSVDDOVPTVDE","short_pith_number":"pith:MJAMBL5D","canonical_record":{"source":{"id":"1708.01749","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-05T10:58:19Z","cross_cats_sorted":[],"title_canon_sha256":"3fb84cfe2778287244a811a4244c187685d474de5cd1c152c94dae703f2fb425","abstract_canon_sha256":"54ccddb324313b9cecebd27d8c50ca70604e56bf54d15411e152434cef6ee422"},"schema_version":"1.0"},"canonical_sha256":"6240c0afa3fdf7f49192a8c6eabe75191c80e53eef78cd641108572793d7e055","source":{"kind":"arxiv","id":"1708.01749","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.01749","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"arxiv_version","alias_value":"1708.01749v1","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01749","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"pith_short_12","alias_value":"MJAMBL5D7X37","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"pith_short_16","alias_value":"MJAMBL5D7X37JEMS","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"pith_short_8","alias_value":"MJAMBL5D","created_at":"2026-07-05T01:05:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:MJAMBL5D7X37JEMSVDDOVPTVDE","target":"record","payload":{"canonical_record":{"source":{"id":"1708.01749","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-05T10:58:19Z","cross_cats_sorted":[],"title_canon_sha256":"3fb84cfe2778287244a811a4244c187685d474de5cd1c152c94dae703f2fb425","abstract_canon_sha256":"54ccddb324313b9cecebd27d8c50ca70604e56bf54d15411e152434cef6ee422"},"schema_version":"1.0"},"canonical_sha256":"6240c0afa3fdf7f49192a8c6eabe75191c80e53eef78cd641108572793d7e055","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:05:07.772514Z","signature_b64":"ISbT/MOXG620GOWbYS9OF1NhUkApJmBVIX2YXK7dZroRtRPgbTMO5pS6bt6od+cO3iRrsUKD3s+mrzGue4uADg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6240c0afa3fdf7f49192a8c6eabe75191c80e53eef78cd641108572793d7e055","last_reissued_at":"2026-07-05T01:05:07.771983Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:05:07.771983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.01749","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":"2026-07-05T01:05:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dd1bPgOO88l+oJ8LbElqJm0/5SyXHo1j5u07CS1x/Uf1gZQPUJaBe94YNKNl3YF5J2+Y19ClzeDM6m4Uu8juAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T07:50:26.590657Z"},"content_sha256":"616406ebfead51402f0b25bc32b39c286f3e48a225dd04bbf035778414aa1681","schema_version":"1.0","event_id":"sha256:616406ebfead51402f0b25bc32b39c286f3e48a225dd04bbf035778414aa1681"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:MJAMBL5D7X37JEMSVDDOVPTVDE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haitian Zheng, Juergen Gall, Lu Fang, Mengqi Ji, Yebin Liu","submitted_at":"2017-08-05T10:58:19Z","abstract_excerpt":"This paper proposes an end-to-end learning framework for multiview stereopsis. We term the network SurfaceNet. It takes a set of images and their corresponding camera parameters as input and directly infers the 3D model. The key advantage of the framework is that both photo-consistency as well geometric relations of the surface structure can be directly learned for the purpose of multiview stereopsis in an end-to-end fashion. SurfaceNet is a fully 3D convolutional network which is achieved by encoding the camera parameters together with the images in a 3D voxel representation. We evaluate Surf"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01749","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/1708.01749/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":"2026-07-05T01:05:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mFcjQ5f8MhZmpbv6DnxoczfTL/iufRYhfPf5IWIlLhWf95x1XcquPekQ8MgPyYE+CnSJh7gVzTrq6la3rl5aCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T07:50:26.591168Z"},"content_sha256":"d17590cf84ba49afc4a6d7fb6e7b0274376de77d8445ed70fe5c7063bc20ece2","schema_version":"1.0","event_id":"sha256:d17590cf84ba49afc4a6d7fb6e7b0274376de77d8445ed70fe5c7063bc20ece2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MJAMBL5D7X37JEMSVDDOVPTVDE/bundle.json","state_url":"https://pith.science/pith/MJAMBL5D7X37JEMSVDDOVPTVDE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MJAMBL5D7X37JEMSVDDOVPTVDE/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":"2026-08-15T07:50:26Z","links":{"resolver":"https://pith.science/pith/MJAMBL5D7X37JEMSVDDOVPTVDE","bundle":"https://pith.science/pith/MJAMBL5D7X37JEMSVDDOVPTVDE/bundle.json","state":"https://pith.science/pith/MJAMBL5D7X37JEMSVDDOVPTVDE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MJAMBL5D7X37JEMSVDDOVPTVDE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:MJAMBL5D7X37JEMSVDDOVPTVDE","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":"54ccddb324313b9cecebd27d8c50ca70604e56bf54d15411e152434cef6ee422","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-05T10:58:19Z","title_canon_sha256":"3fb84cfe2778287244a811a4244c187685d474de5cd1c152c94dae703f2fb425"},"schema_version":"1.0","source":{"id":"1708.01749","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.01749","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"arxiv_version","alias_value":"1708.01749v1","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01749","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"pith_short_12","alias_value":"MJAMBL5D7X37","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"pith_short_16","alias_value":"MJAMBL5D7X37JEMS","created_at":"2026-07-05T01:05:07Z"},{"alias_kind":"pith_short_8","alias_value":"MJAMBL5D","created_at":"2026-07-05T01:05:07Z"}],"graph_snapshots":[{"event_id":"sha256:d17590cf84ba49afc4a6d7fb6e7b0274376de77d8445ed70fe5c7063bc20ece2","target":"graph","created_at":"2026-07-05T01:05:07Z","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/1708.01749/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper proposes an end-to-end learning framework for multiview stereopsis. We term the network SurfaceNet. It takes a set of images and their corresponding camera parameters as input and directly infers the 3D model. The key advantage of the framework is that both photo-consistency as well geometric relations of the surface structure can be directly learned for the purpose of multiview stereopsis in an end-to-end fashion. SurfaceNet is a fully 3D convolutional network which is achieved by encoding the camera parameters together with the images in a 3D voxel representation. We evaluate Surf","authors_text":"Haitian Zheng, Juergen Gall, Lu Fang, Mengqi Ji, Yebin Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-05T10:58:19Z","title":"SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01749","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":"sha256:616406ebfead51402f0b25bc32b39c286f3e48a225dd04bbf035778414aa1681","target":"record","created_at":"2026-07-05T01:05:07Z","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":"54ccddb324313b9cecebd27d8c50ca70604e56bf54d15411e152434cef6ee422","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-05T10:58:19Z","title_canon_sha256":"3fb84cfe2778287244a811a4244c187685d474de5cd1c152c94dae703f2fb425"},"schema_version":"1.0","source":{"id":"1708.01749","kind":"arxiv","version":1}},"canonical_sha256":"6240c0afa3fdf7f49192a8c6eabe75191c80e53eef78cd641108572793d7e055","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6240c0afa3fdf7f49192a8c6eabe75191c80e53eef78cd641108572793d7e055","first_computed_at":"2026-07-05T01:05:07.771983Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:05:07.771983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ISbT/MOXG620GOWbYS9OF1NhUkApJmBVIX2YXK7dZroRtRPgbTMO5pS6bt6od+cO3iRrsUKD3s+mrzGue4uADg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:05:07.772514Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.01749","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:616406ebfead51402f0b25bc32b39c286f3e48a225dd04bbf035778414aa1681","sha256:d17590cf84ba49afc4a6d7fb6e7b0274376de77d8445ed70fe5c7063bc20ece2"],"state_sha256":"9afb0e4d93e67369465deddb7998fdaac139158ce2077d52455306ba3c9f85c8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l++fe5B51m4/kLlWg1H+kM4Oi3J8E9heFQ1c7ZvyG3MJqCq67Xu19BOkRB9zO5dAdFwCfvAmgP/+7zqnjnnLBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T07:50:26.595441Z","bundle_sha256":"97224bd091362fe67c65aaf1c3721771c94a821005717b99f03b4d450aef4a55"}}