{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:IOTGZAPXHLOYR5KXRA24DDMSCI","short_pith_number":"pith:IOTGZAPX","schema_version":"1.0","canonical_sha256":"43a66c81f73add88f5578835c18d921218bf5fab067fea3a1ca1cd9a2b70bb37","source":{"kind":"arxiv","id":"2403.04899","version":2},"attestation_state":"computed","paper":{"title":"Towards Scene Graph Anticipation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Parag Singla, Rohith Peddi, Saksham Singh, Saurabh, Vibhav Gogate","submitted_at":"2024-03-07T21:08:51Z","abstract_excerpt":"Spatio-temporal scene graphs represent interactions in a video by decomposing scenes into individual objects and their pair-wise temporal relationships. Long-term anticipation of the fine-grained pair-wise relationships between objects is a challenging problem. To this end, we introduce the task of Scene Graph Anticipation (SGA). We adapt state-of-the-art scene graph generation methods as baselines to anticipate future pair-wise relationships between objects and propose a novel approach SceneSayer. In SceneSayer, we leverage object-centric representations of relationships to reason about the o"},"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":"2403.04899","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-07T21:08:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"7fa26e3b6776a1dab449ef73ccbab9c709e36840e834de8a75c25839bba3c00c","abstract_canon_sha256":"7b90d2615fcbe4c7c67a4596a92a054c52ceb2c85950a685219b8ba928a25823"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:46:07.434928Z","signature_b64":"d1zsSlmTnO9nUfu+Jlxgi5zDB9rTdHwGWF9xytgF+NQPdvaTpUevf/tsQSkp458TCKFw3vPWiidc2WZ5DMCeDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"43a66c81f73add88f5578835c18d921218bf5fab067fea3a1ca1cd9a2b70bb37","last_reissued_at":"2026-07-05T08:46:07.434483Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:46:07.434483Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards Scene Graph Anticipation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Parag Singla, Rohith Peddi, Saksham Singh, Saurabh, Vibhav Gogate","submitted_at":"2024-03-07T21:08:51Z","abstract_excerpt":"Spatio-temporal scene graphs represent interactions in a video by decomposing scenes into individual objects and their pair-wise temporal relationships. Long-term anticipation of the fine-grained pair-wise relationships between objects is a challenging problem. To this end, we introduce the task of Scene Graph Anticipation (SGA). We adapt state-of-the-art scene graph generation methods as baselines to anticipate future pair-wise relationships between objects and propose a novel approach SceneSayer. In SceneSayer, we leverage object-centric representations of relationships to reason about the o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.04899","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/2403.04899/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":"2403.04899","created_at":"2026-07-05T08:46:07.434541+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.04899v2","created_at":"2026-07-05T08:46:07.434541+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.04899","created_at":"2026-07-05T08:46:07.434541+00:00"},{"alias_kind":"pith_short_12","alias_value":"IOTGZAPXHLOY","created_at":"2026-07-05T08:46:07.434541+00:00"},{"alias_kind":"pith_short_16","alias_value":"IOTGZAPXHLOYR5KX","created_at":"2026-07-05T08:46:07.434541+00:00"},{"alias_kind":"pith_short_8","alias_value":"IOTGZAPX","created_at":"2026-07-05T08:46:07.434541+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/IOTGZAPXHLOYR5KXRA24DDMSCI","json":"https://pith.science/pith/IOTGZAPXHLOYR5KXRA24DDMSCI.json","graph_json":"https://pith.science/api/pith-number/IOTGZAPXHLOYR5KXRA24DDMSCI/graph.json","events_json":"https://pith.science/api/pith-number/IOTGZAPXHLOYR5KXRA24DDMSCI/events.json","paper":"https://pith.science/paper/IOTGZAPX"},"agent_actions":{"view_html":"https://pith.science/pith/IOTGZAPXHLOYR5KXRA24DDMSCI","download_json":"https://pith.science/pith/IOTGZAPXHLOYR5KXRA24DDMSCI.json","view_paper":"https://pith.science/paper/IOTGZAPX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.04899&json=true","fetch_graph":"https://pith.science/api/pith-number/IOTGZAPXHLOYR5KXRA24DDMSCI/graph.json","fetch_events":"https://pith.science/api/pith-number/IOTGZAPXHLOYR5KXRA24DDMSCI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IOTGZAPXHLOYR5KXRA24DDMSCI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IOTGZAPXHLOYR5KXRA24DDMSCI/action/storage_attestation","attest_author":"https://pith.science/pith/IOTGZAPXHLOYR5KXRA24DDMSCI/action/author_attestation","sign_citation":"https://pith.science/pith/IOTGZAPXHLOYR5KXRA24DDMSCI/action/citation_signature","submit_replication":"https://pith.science/pith/IOTGZAPXHLOYR5KXRA24DDMSCI/action/replication_record"}},"created_at":"2026-07-05T08:46:07.434541+00:00","updated_at":"2026-07-05T08:46:07.434541+00:00"}