{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:ZS6YVNWRTNHV3BQJNQIBIW2DNV","short_pith_number":"pith:ZS6YVNWR","schema_version":"1.0","canonical_sha256":"ccbd8ab6d19b4f5d86096c10145b436d4e96f828a460447f9fc243c4f47cd3fb","source":{"kind":"arxiv","id":"2607.09125","version":1},"attestation_state":"computed","paper":{"title":"4D Human-Scene Reconstruction from Low-Overlap Captures","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Daneul Kim, Jaesik Park, Minhyuk Hwang, Sangmin Kim, Seunguk Do","submitted_at":"2026-07-10T06:30:45Z","abstract_excerpt":"Existing volumetric capture of dynamic human performance achieves high fidelity with dense camera arrays. However, in real-world scenarios, only a handful of low-overlap cameras are available, which degrades the output quality and leaves large areas unobserved. Recent 4D reconstruction methods have focused on low-overlap settings, yet they still produce noticeable artifacts in under-observed regions. Video diffusion models have emerged as another option, but they show geometrically inconsistent results for humans. To address these limitations, we propose StudioRecon, a pipeline that reconstruc"},"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":"2607.09125","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-10T06:30:45Z","cross_cats_sorted":[],"title_canon_sha256":"81d6663b92fb1fd1cf3f3e4cd3b66dba60f19d56d6ef1084227f64c86ee77aa0","abstract_canon_sha256":"5a81f6df94142e5c6fb9d152a2ce2aa3b93f47a60d8724416cd885ad49d8ffd7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-13T01:18:44.453515Z","signature_b64":"jWcgSqRpTXqca3nMSNItYh+IIlEtAtHlzEhpy8qlT/Y0U4ajqVOm7UErXYjYAZLiCb9iG8xgD0hzisKIqJXMCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ccbd8ab6d19b4f5d86096c10145b436d4e96f828a460447f9fc243c4f47cd3fb","last_reissued_at":"2026-07-13T01:18:44.452133Z","signature_status":"signed_v1","first_computed_at":"2026-07-13T01:18:44.452133Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"4D Human-Scene Reconstruction from Low-Overlap Captures","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Daneul Kim, Jaesik Park, Minhyuk Hwang, Sangmin Kim, Seunguk Do","submitted_at":"2026-07-10T06:30:45Z","abstract_excerpt":"Existing volumetric capture of dynamic human performance achieves high fidelity with dense camera arrays. However, in real-world scenarios, only a handful of low-overlap cameras are available, which degrades the output quality and leaves large areas unobserved. Recent 4D reconstruction methods have focused on low-overlap settings, yet they still produce noticeable artifacts in under-observed regions. Video diffusion models have emerged as another option, but they show geometrically inconsistent results for humans. To address these limitations, we propose StudioRecon, a pipeline that reconstruc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.09125","kind":"arxiv","version":1},"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/2607.09125/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":"2607.09125","created_at":"2026-07-13T01:18:44.452763+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.09125v1","created_at":"2026-07-13T01:18:44.452763+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.09125","created_at":"2026-07-13T01:18:44.452763+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZS6YVNWRTNHV","created_at":"2026-07-13T01:18:44.452763+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZS6YVNWRTNHV3BQJ","created_at":"2026-07-13T01:18:44.452763+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZS6YVNWR","created_at":"2026-07-13T01:18:44.452763+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/ZS6YVNWRTNHV3BQJNQIBIW2DNV","json":"https://pith.science/pith/ZS6YVNWRTNHV3BQJNQIBIW2DNV.json","graph_json":"https://pith.science/api/pith-number/ZS6YVNWRTNHV3BQJNQIBIW2DNV/graph.json","events_json":"https://pith.science/api/pith-number/ZS6YVNWRTNHV3BQJNQIBIW2DNV/events.json","paper":"https://pith.science/paper/ZS6YVNWR"},"agent_actions":{"view_html":"https://pith.science/pith/ZS6YVNWRTNHV3BQJNQIBIW2DNV","download_json":"https://pith.science/pith/ZS6YVNWRTNHV3BQJNQIBIW2DNV.json","view_paper":"https://pith.science/paper/ZS6YVNWR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.09125&json=true","fetch_graph":"https://pith.science/api/pith-number/ZS6YVNWRTNHV3BQJNQIBIW2DNV/graph.json","fetch_events":"https://pith.science/api/pith-number/ZS6YVNWRTNHV3BQJNQIBIW2DNV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZS6YVNWRTNHV3BQJNQIBIW2DNV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZS6YVNWRTNHV3BQJNQIBIW2DNV/action/storage_attestation","attest_author":"https://pith.science/pith/ZS6YVNWRTNHV3BQJNQIBIW2DNV/action/author_attestation","sign_citation":"https://pith.science/pith/ZS6YVNWRTNHV3BQJNQIBIW2DNV/action/citation_signature","submit_replication":"https://pith.science/pith/ZS6YVNWRTNHV3BQJNQIBIW2DNV/action/replication_record"}},"created_at":"2026-07-13T01:18:44.452763+00:00","updated_at":"2026-07-13T01:18:44.452763+00:00"}