{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:TRBAZZLWFG3MA3CHZJUWVSDT4O","short_pith_number":"pith:TRBAZZLW","schema_version":"1.0","canonical_sha256":"9c420ce57629b6c06c47ca696ac873e38b0cf1a0fb1822284f677f1e31b67b18","source":{"kind":"arxiv","id":"2011.12100","version":2},"attestation_state":"computed","paper":{"title":"GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Andreas Geiger, Michael Niemeyer","submitted_at":"2020-11-24T14:14:15Z","abstract_excerpt":"Deep generative models allow for photorealistic image synthesis at high resolutions. But for many applications, this is not enough: content creation also needs to be controllable. While several recent works investigate how to disentangle underlying factors of variation in the data, most of them operate in 2D and hence ignore that our world is three-dimensional. Further, only few works consider the compositional nature of scenes. Our key hypothesis is that incorporating a compositional 3D scene representation into the generative model leads to more controllable image synthesis. Representing sce"},"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":"2011.12100","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-24T14:14:15Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"d28f73f7daba95e4ff0cb0bd01cf8cf7f83ae90ea0027b9b5a1421184619fb8c","abstract_canon_sha256":"d3953dc091cd8fe953eec5f3aa13c3110fc8d37f4df2167d6612ee78477ef456"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:36:09.006388Z","signature_b64":"nYuBk5D89YDjiFkbHzt6tx8ZdjpHUTdK9DSQ1vLHAr2sjC4rVzDPzu5RztSrDISZAE/wbotYVKptGACg8KsHBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c420ce57629b6c06c47ca696ac873e38b0cf1a0fb1822284f677f1e31b67b18","last_reissued_at":"2026-07-05T02:36:09.005935Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:36:09.005935Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Andreas Geiger, Michael Niemeyer","submitted_at":"2020-11-24T14:14:15Z","abstract_excerpt":"Deep generative models allow for photorealistic image synthesis at high resolutions. But for many applications, this is not enough: content creation also needs to be controllable. While several recent works investigate how to disentangle underlying factors of variation in the data, most of them operate in 2D and hence ignore that our world is three-dimensional. Further, only few works consider the compositional nature of scenes. Our key hypothesis is that incorporating a compositional 3D scene representation into the generative model leads to more controllable image synthesis. Representing sce"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.12100","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/2011.12100/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":"2011.12100","created_at":"2026-07-05T02:36:09.005997+00:00"},{"alias_kind":"arxiv_version","alias_value":"2011.12100v2","created_at":"2026-07-05T02:36:09.005997+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.12100","created_at":"2026-07-05T02:36:09.005997+00:00"},{"alias_kind":"pith_short_12","alias_value":"TRBAZZLWFG3M","created_at":"2026-07-05T02:36:09.005997+00:00"},{"alias_kind":"pith_short_16","alias_value":"TRBAZZLWFG3MA3CH","created_at":"2026-07-05T02:36:09.005997+00:00"},{"alias_kind":"pith_short_8","alias_value":"TRBAZZLW","created_at":"2026-07-05T02:36:09.005997+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/TRBAZZLWFG3MA3CHZJUWVSDT4O","json":"https://pith.science/pith/TRBAZZLWFG3MA3CHZJUWVSDT4O.json","graph_json":"https://pith.science/api/pith-number/TRBAZZLWFG3MA3CHZJUWVSDT4O/graph.json","events_json":"https://pith.science/api/pith-number/TRBAZZLWFG3MA3CHZJUWVSDT4O/events.json","paper":"https://pith.science/paper/TRBAZZLW"},"agent_actions":{"view_html":"https://pith.science/pith/TRBAZZLWFG3MA3CHZJUWVSDT4O","download_json":"https://pith.science/pith/TRBAZZLWFG3MA3CHZJUWVSDT4O.json","view_paper":"https://pith.science/paper/TRBAZZLW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2011.12100&json=true","fetch_graph":"https://pith.science/api/pith-number/TRBAZZLWFG3MA3CHZJUWVSDT4O/graph.json","fetch_events":"https://pith.science/api/pith-number/TRBAZZLWFG3MA3CHZJUWVSDT4O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TRBAZZLWFG3MA3CHZJUWVSDT4O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TRBAZZLWFG3MA3CHZJUWVSDT4O/action/storage_attestation","attest_author":"https://pith.science/pith/TRBAZZLWFG3MA3CHZJUWVSDT4O/action/author_attestation","sign_citation":"https://pith.science/pith/TRBAZZLWFG3MA3CHZJUWVSDT4O/action/citation_signature","submit_replication":"https://pith.science/pith/TRBAZZLWFG3MA3CHZJUWVSDT4O/action/replication_record"}},"created_at":"2026-07-05T02:36:09.005997+00:00","updated_at":"2026-07-05T02:36:09.005997+00:00"}