{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:DTKWIGQW5YQM6EVLEWY6J5ALCV","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":"699d63e39f2615aa18610d2376b3a8e3e44ed445807d801540987dcab243c2c2","cross_cats_sorted":["cs.MM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-06T16:18:15Z","title_canon_sha256":"835b2f72aa47e4cef04d3afa435981942263a25aa869c4f60cfea9c4562e24cd"},"schema_version":"1.0","source":{"id":"2206.02717","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.02717","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"arxiv_version","alias_value":"2206.02717v2","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.02717","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_12","alias_value":"DTKWIGQW5YQM","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_16","alias_value":"DTKWIGQW5YQM6EVL","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_8","alias_value":"DTKWIGQW","created_at":"2026-07-05T10:16:04Z"}],"graph_snapshots":[{"event_id":"sha256:968ac7e469082e83473569afdc6946ebc49cc566b9c7d82e12ebae6c6d2b77d0","target":"graph","created_at":"2026-07-05T10:16:04Z","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/2206.02717/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Person image generation is an intriguing yet challenging problem. However, this task becomes even more difficult under constrained situations. In this work, we propose a novel pipeline to generate and insert contextually relevant person images into an existing scene while preserving the global semantics. More specifically, we aim to insert a person such that the location, pose, and scale of the person being inserted blends in with the existing persons in the scene. Our method uses three individual networks in a sequential pipeline. At first, we predict the potential location and the skeletal s","authors_text":"Michael Blumenstein, Prasun Roy, Saumik Bhattacharya, Subhankar Ghosh, Umapada Pal","cross_cats":["cs.MM"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-06T16:18:15Z","title":"Scene Aware Person Image Generation through Global Contextual Conditioning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.02717","kind":"arxiv","version":2},"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:d54fa51f6bba54551e1ade2035d76aaef5e5be834c80df9d7bb8886a739ad8b7","target":"record","created_at":"2026-07-05T10:16:04Z","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":"699d63e39f2615aa18610d2376b3a8e3e44ed445807d801540987dcab243c2c2","cross_cats_sorted":["cs.MM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-06T16:18:15Z","title_canon_sha256":"835b2f72aa47e4cef04d3afa435981942263a25aa869c4f60cfea9c4562e24cd"},"schema_version":"1.0","source":{"id":"2206.02717","kind":"arxiv","version":2}},"canonical_sha256":"1cd5641a16ee20cf12ab25b1e4f40b157f8cc1a16d541a9f21ba933b6b6b61fe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1cd5641a16ee20cf12ab25b1e4f40b157f8cc1a16d541a9f21ba933b6b6b61fe","first_computed_at":"2026-07-05T10:16:04.808491Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:16:04.808491Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xxDftXQWszcg6Pn9hFbfjLtHVjo5uflGVYPiafUiaphc2FASpfH+qAGe8wLAjn7Y/QksKb9LnxFFBmcjo5jABQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:16:04.808900Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.02717","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d54fa51f6bba54551e1ade2035d76aaef5e5be834c80df9d7bb8886a739ad8b7","sha256:968ac7e469082e83473569afdc6946ebc49cc566b9c7d82e12ebae6c6d2b77d0"],"state_sha256":"a08782ed8d3320051d41ccb8a7b600c0ebd5974aa6fdacda2690ae9292ae87a1"}