{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:ZYZH5Q53HGZAN5UEMCPQXAYUSN","short_pith_number":"pith:ZYZH5Q53","schema_version":"1.0","canonical_sha256":"ce327ec3bb39b206f684609f0b831493753ecf9631607642a6caf5a9fa0ef976","source":{"kind":"arxiv","id":"2304.13681","version":2},"attestation_state":"computed","paper":{"title":"Ray Conditioning: Trading Photo-consistency for Photo-realism in Multi-view Image Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abe Davis, Eric Ming Chen, Kai Zhang, Ruyu Yan, Sidhanth Holalkere","submitted_at":"2023-04-26T16:54:10Z","abstract_excerpt":"Multi-view image generation attracts particular attention these days due to its promising 3D-related applications, e.g., image viewpoint editing. Most existing methods follow a paradigm where a 3D representation is first synthesized, and then rendered into 2D images to ensure photo-consistency across viewpoints. However, such explicit bias for photo-consistency sacrifices photo-realism, causing geometry artifacts and loss of fine-scale details when these methods are applied to edit real images. To address this issue, we propose ray conditioning, a geometry-free alternative that relaxes the pho"},"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":"2304.13681","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-26T16:54:10Z","cross_cats_sorted":[],"title_canon_sha256":"0f645564c0303037269d13e86b38ba8f50cd19bb95d3e2db1e16b9cfd7f6ac5f","abstract_canon_sha256":"8cb3a5e8b5fadc8ec6eac5da3faf71f3c4bfecb00c2a13bd5d1879dc01382fdb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:47:20.672922Z","signature_b64":"bn3c0jNZmQm15rTEejbP4h+Onl1g6DNay2slGTtBYpGGuwf6wvzHSy/Fr+RPbcDX5GHcJ6a9GLtPRqvPWCdZDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce327ec3bb39b206f684609f0b831493753ecf9631607642a6caf5a9fa0ef976","last_reissued_at":"2026-07-05T06:47:20.672262Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:47:20.672262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Ray Conditioning: Trading Photo-consistency for Photo-realism in Multi-view Image Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abe Davis, Eric Ming Chen, Kai Zhang, Ruyu Yan, Sidhanth Holalkere","submitted_at":"2023-04-26T16:54:10Z","abstract_excerpt":"Multi-view image generation attracts particular attention these days due to its promising 3D-related applications, e.g., image viewpoint editing. Most existing methods follow a paradigm where a 3D representation is first synthesized, and then rendered into 2D images to ensure photo-consistency across viewpoints. However, such explicit bias for photo-consistency sacrifices photo-realism, causing geometry artifacts and loss of fine-scale details when these methods are applied to edit real images. To address this issue, we propose ray conditioning, a geometry-free alternative that relaxes the pho"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.13681","kind":"arxiv","version":2},"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/2304.13681/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2304.13681","created_at":"2026-07-05T06:47:20.672349+00:00"},{"alias_kind":"arxiv_version","alias_value":"2304.13681v2","created_at":"2026-07-05T06:47:20.672349+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.13681","created_at":"2026-07-05T06:47:20.672349+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZYZH5Q53HGZA","created_at":"2026-07-05T06:47:20.672349+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZYZH5Q53HGZAN5UE","created_at":"2026-07-05T06:47:20.672349+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZYZH5Q53","created_at":"2026-07-05T06:47:20.672349+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2404.02101","citing_title":"CameraCtrl: Enabling Camera Control for Text-to-Video Generation","ref_index":26,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN","json":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN.json","graph_json":"https://pith.science/api/pith-number/ZYZH5Q53HGZAN5UEMCPQXAYUSN/graph.json","events_json":"https://pith.science/api/pith-number/ZYZH5Q53HGZAN5UEMCPQXAYUSN/events.json","paper":"https://pith.science/paper/ZYZH5Q53"},"agent_actions":{"view_html":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN","download_json":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN.json","view_paper":"https://pith.science/paper/ZYZH5Q53","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2304.13681&json=true","fetch_graph":"https://pith.science/api/pith-number/ZYZH5Q53HGZAN5UEMCPQXAYUSN/graph.json","fetch_events":"https://pith.science/api/pith-number/ZYZH5Q53HGZAN5UEMCPQXAYUSN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN/action/storage_attestation","attest_author":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN/action/author_attestation","sign_citation":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN/action/citation_signature","submit_replication":"https://pith.science/pith/ZYZH5Q53HGZAN5UEMCPQXAYUSN/action/replication_record"}},"created_at":"2026-07-05T06:47:20.672349+00:00","updated_at":"2026-07-05T06:47:20.672349+00:00"}