{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:RMS2BYBIVLOKUEBBWQRX6RLTZX","short_pith_number":"pith:RMS2BYBI","canonical_record":{"source":{"id":"2208.10769","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-23T07:00:44Z","cross_cats_sorted":[],"title_canon_sha256":"1e9b2911bc9368a1a68286c22b0118ec774236a7a2588c470912d29b4319ed53","abstract_canon_sha256":"74fead5eea38fd7480f68eaa03bd0a9a00bbfa13ff1cfee25e02d8fe55c1d92e"},"schema_version":"1.0"},"canonical_sha256":"8b25a0e028aadcaa1021b4237f4573cdf27fca01ff7c111a5cbc5b46482159be","source":{"kind":"arxiv","id":"2208.10769","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.10769","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"arxiv_version","alias_value":"2208.10769v2","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.10769","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"pith_short_12","alias_value":"RMS2BYBIVLOK","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"pith_short_16","alias_value":"RMS2BYBIVLOKUEBB","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"pith_short_8","alias_value":"RMS2BYBI","created_at":"2026-07-05T07:53:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:RMS2BYBIVLOKUEBBWQRX6RLTZX","target":"record","payload":{"canonical_record":{"source":{"id":"2208.10769","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-23T07:00:44Z","cross_cats_sorted":[],"title_canon_sha256":"1e9b2911bc9368a1a68286c22b0118ec774236a7a2588c470912d29b4319ed53","abstract_canon_sha256":"74fead5eea38fd7480f68eaa03bd0a9a00bbfa13ff1cfee25e02d8fe55c1d92e"},"schema_version":"1.0"},"canonical_sha256":"8b25a0e028aadcaa1021b4237f4573cdf27fca01ff7c111a5cbc5b46482159be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:45.878064Z","signature_b64":"lLdJyyeO+xErG0+amXzt94Pm+sCE0QB5EJyj+iE/QqG+mOhc2cTr22Lkjgw+i94qKCf2zWkX6+bnD/eAJdmoAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8b25a0e028aadcaa1021b4237f4573cdf27fca01ff7c111a5cbc5b46482159be","last_reissued_at":"2026-07-05T07:53:45.877558Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:45.877558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.10769","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:53:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8qmsAJUeL9JqlXjqecVkDVabz7xPfRVthoTFkvsupchu4mTepHuShTP/+1HmoS6PfqRXQVbbAX8Z/AdYMMJpDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T04:53:35.525329Z"},"content_sha256":"456fcb31cdc819f4e1a34a71f061579496d21d32cb27c75248ff4e673e452b2e","schema_version":"1.0","event_id":"sha256:456fcb31cdc819f4e1a34a71f061579496d21d32cb27c75248ff4e673e452b2e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:RMS2BYBIVLOKUEBBWQRX6RLTZX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PIFu for the Real World: A Self-supervised Framework to Reconstruct Dressed Human from Single-view Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Di Kang, Dong Du, Jingqi Dong, Linchao Bao, Xiaoguang Han, Yushuang Wu, Zhangyang Xiong","submitted_at":"2022-08-23T07:00:44Z","abstract_excerpt":"It is very challenging to accurately reconstruct sophisticated human geometry caused by various poses and garments from a single image. Recently, works based on pixel-aligned implicit function (PIFu) have made a big step and achieved state-of-the-art fidelity on image-based 3D human digitization. However, the training of PIFu relies heavily on expensive and limited 3D ground truth data (i.e. synthetic data), thus hindering its generalization to more diverse real world images. In this work, we propose an end-to-end self-supervised network named SelfPIFu to utilize abundant and diverse in-the-wi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.10769","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/2208.10769/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:53:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eVFBhDl8E0dvj/W/cbbHN/79c3RRIU4MagToLgPnjmfGQf5LUVB8SVwvIRq9dHjI4higCYS5g/+rmQtaJWLFDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T04:53:35.525714Z"},"content_sha256":"153c83590cfe79ac0e8afeb4633d38656222518e98b595938cfc0f6671e77371","schema_version":"1.0","event_id":"sha256:153c83590cfe79ac0e8afeb4633d38656222518e98b595938cfc0f6671e77371"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RMS2BYBIVLOKUEBBWQRX6RLTZX/bundle.json","state_url":"https://pith.science/pith/RMS2BYBIVLOKUEBBWQRX6RLTZX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RMS2BYBIVLOKUEBBWQRX6RLTZX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-13T04:53:35Z","links":{"resolver":"https://pith.science/pith/RMS2BYBIVLOKUEBBWQRX6RLTZX","bundle":"https://pith.science/pith/RMS2BYBIVLOKUEBBWQRX6RLTZX/bundle.json","state":"https://pith.science/pith/RMS2BYBIVLOKUEBBWQRX6RLTZX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RMS2BYBIVLOKUEBBWQRX6RLTZX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:RMS2BYBIVLOKUEBBWQRX6RLTZX","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":"74fead5eea38fd7480f68eaa03bd0a9a00bbfa13ff1cfee25e02d8fe55c1d92e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-23T07:00:44Z","title_canon_sha256":"1e9b2911bc9368a1a68286c22b0118ec774236a7a2588c470912d29b4319ed53"},"schema_version":"1.0","source":{"id":"2208.10769","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.10769","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"arxiv_version","alias_value":"2208.10769v2","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.10769","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"pith_short_12","alias_value":"RMS2BYBIVLOK","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"pith_short_16","alias_value":"RMS2BYBIVLOKUEBB","created_at":"2026-07-05T07:53:45Z"},{"alias_kind":"pith_short_8","alias_value":"RMS2BYBI","created_at":"2026-07-05T07:53:45Z"}],"graph_snapshots":[{"event_id":"sha256:153c83590cfe79ac0e8afeb4633d38656222518e98b595938cfc0f6671e77371","target":"graph","created_at":"2026-07-05T07:53:45Z","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/2208.10769/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"It is very challenging to accurately reconstruct sophisticated human geometry caused by various poses and garments from a single image. Recently, works based on pixel-aligned implicit function (PIFu) have made a big step and achieved state-of-the-art fidelity on image-based 3D human digitization. However, the training of PIFu relies heavily on expensive and limited 3D ground truth data (i.e. synthetic data), thus hindering its generalization to more diverse real world images. In this work, we propose an end-to-end self-supervised network named SelfPIFu to utilize abundant and diverse in-the-wi","authors_text":"Di Kang, Dong Du, Jingqi Dong, Linchao Bao, Xiaoguang Han, Yushuang Wu, Zhangyang Xiong","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-23T07:00:44Z","title":"PIFu for the Real World: A Self-supervised Framework to Reconstruct Dressed Human from Single-view Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.10769","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":"sha256:456fcb31cdc819f4e1a34a71f061579496d21d32cb27c75248ff4e673e452b2e","target":"record","created_at":"2026-07-05T07:53:45Z","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":"74fead5eea38fd7480f68eaa03bd0a9a00bbfa13ff1cfee25e02d8fe55c1d92e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-23T07:00:44Z","title_canon_sha256":"1e9b2911bc9368a1a68286c22b0118ec774236a7a2588c470912d29b4319ed53"},"schema_version":"1.0","source":{"id":"2208.10769","kind":"arxiv","version":2}},"canonical_sha256":"8b25a0e028aadcaa1021b4237f4573cdf27fca01ff7c111a5cbc5b46482159be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8b25a0e028aadcaa1021b4237f4573cdf27fca01ff7c111a5cbc5b46482159be","first_computed_at":"2026-07-05T07:53:45.877558Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:53:45.877558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lLdJyyeO+xErG0+amXzt94Pm+sCE0QB5EJyj+iE/QqG+mOhc2cTr22Lkjgw+i94qKCf2zWkX6+bnD/eAJdmoAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:53:45.878064Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.10769","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:456fcb31cdc819f4e1a34a71f061579496d21d32cb27c75248ff4e673e452b2e","sha256:153c83590cfe79ac0e8afeb4633d38656222518e98b595938cfc0f6671e77371"],"state_sha256":"742269630e3e58a9b36f72258147c797c1cec002fb790dda546d099af6da45df"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BBv2seTc6Wv/ScgPomISzUnhV9FwJe61HIOmqBm9D9dygln1+Y8hsF2HFPpQQC3eigpPcMG3j5+84bdPN9F5Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T04:53:35.527890Z","bundle_sha256":"d9d8604b3b932b339b39beb0c05eafe83c7151ab304ec6a14648f0f430580149"}}