{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:IXBT7MJAWCWXOTRCP3UKZI3HUA","short_pith_number":"pith:IXBT7MJA","schema_version":"1.0","canonical_sha256":"45c33fb120b0ad774e227ee8aca367a03970763a20562297f7ee34b649f536e7","source":{"kind":"arxiv","id":"1605.03557","version":3},"attestation_state":"computed","paper":{"title":"View Synthesis by Appearance Flow","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexei A. Efros, Jitendra Malik, Shubham Tulsiani, Tinghui Zhou, Weilun Sun","submitted_at":"2016-05-11T19:16:24Z","abstract_excerpt":"We address the problem of novel view synthesis: given an input image, synthesizing new images of the same object or scene observed from arbitrary viewpoints. We approach this as a learning task but, critically, instead of learning to synthesize pixels from scratch, we learn to copy them from the input image. Our approach exploits the observation that the visual appearance of different views of the same instance is highly correlated, and such correlation could be explicitly learned by training a convolutional neural network (CNN) to predict appearance flows -- 2-D coordinate vectors specifying "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1605.03557","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-05-11T19:16:24Z","cross_cats_sorted":[],"title_canon_sha256":"5188df78a55f4ace318df786cbf992476f8da7615d79bf1faba9fa2e0b86e99e","abstract_canon_sha256":"e9dcccf72d8ac9e5308e9fe63d8c9f8163e476e9e31170c48b958efbfedbd00f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:50:57.159323Z","signature_b64":"Vnd8FohBlxmZ2nkpDH5PoD3NMNb1OIttMvJquVb8jbptQsBJHN+wd8bHceyAtvrYJx2pLaSZYgU/Av8JbgYdDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"45c33fb120b0ad774e227ee8aca367a03970763a20562297f7ee34b649f536e7","last_reissued_at":"2026-05-18T00:50:57.158775Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:50:57.158775Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"View Synthesis by Appearance Flow","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexei A. Efros, Jitendra Malik, Shubham Tulsiani, Tinghui Zhou, Weilun Sun","submitted_at":"2016-05-11T19:16:24Z","abstract_excerpt":"We address the problem of novel view synthesis: given an input image, synthesizing new images of the same object or scene observed from arbitrary viewpoints. We approach this as a learning task but, critically, instead of learning to synthesize pixels from scratch, we learn to copy them from the input image. Our approach exploits the observation that the visual appearance of different views of the same instance is highly correlated, and such correlation could be explicitly learned by training a convolutional neural network (CNN) to predict appearance flows -- 2-D coordinate vectors specifying "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.03557","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1605.03557","created_at":"2026-05-18T00:50:57.158856+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.03557v3","created_at":"2026-05-18T00:50:57.158856+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.03557","created_at":"2026-05-18T00:50:57.158856+00:00"},{"alias_kind":"pith_short_12","alias_value":"IXBT7MJAWCWX","created_at":"2026-05-18T12:30:22.444734+00:00"},{"alias_kind":"pith_short_16","alias_value":"IXBT7MJAWCWXOTRC","created_at":"2026-05-18T12:30:22.444734+00:00"},{"alias_kind":"pith_short_8","alias_value":"IXBT7MJA","created_at":"2026-05-18T12:30:22.444734+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA","json":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA.json","graph_json":"https://pith.science/api/pith-number/IXBT7MJAWCWXOTRCP3UKZI3HUA/graph.json","events_json":"https://pith.science/api/pith-number/IXBT7MJAWCWXOTRCP3UKZI3HUA/events.json","paper":"https://pith.science/paper/IXBT7MJA"},"agent_actions":{"view_html":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA","download_json":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA.json","view_paper":"https://pith.science/paper/IXBT7MJA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.03557&json=true","fetch_graph":"https://pith.science/api/pith-number/IXBT7MJAWCWXOTRCP3UKZI3HUA/graph.json","fetch_events":"https://pith.science/api/pith-number/IXBT7MJAWCWXOTRCP3UKZI3HUA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA/action/storage_attestation","attest_author":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA/action/author_attestation","sign_citation":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA/action/citation_signature","submit_replication":"https://pith.science/pith/IXBT7MJAWCWXOTRCP3UKZI3HUA/action/replication_record"}},"created_at":"2026-05-18T00:50:57.158856+00:00","updated_at":"2026-05-18T00:50:57.158856+00:00"}