{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:T7DE4IHXGWGAFAR4FLI4OKCJSU","short_pith_number":"pith:T7DE4IHX","canonical_record":{"source":{"id":"1906.01963","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-03T19:12:55Z","cross_cats_sorted":[],"title_canon_sha256":"a16fe0c7059eabe3f883c8d998a7e6b2c782056369cbd377eef9a12a2f9e1948","abstract_canon_sha256":"35fa1f61ae88e5aab30044fabf33e90cd696fcd771e4fe101e031abe5355b456"},"schema_version":"1.0"},"canonical_sha256":"9fc64e20f7358c02823c2ad1c72849952455f4a72a8a019980ddd3f997c25c66","source":{"kind":"arxiv","id":"1906.01963","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.01963","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"1906.01963v1","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.01963","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"T7DE4IHXGWGA","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"T7DE4IHXGWGAFAR4","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"T7DE4IHX","created_at":"2026-05-18T12:33:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:T7DE4IHXGWGAFAR4FLI4OKCJSU","target":"record","payload":{"canonical_record":{"source":{"id":"1906.01963","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-03T19:12:55Z","cross_cats_sorted":[],"title_canon_sha256":"a16fe0c7059eabe3f883c8d998a7e6b2c782056369cbd377eef9a12a2f9e1948","abstract_canon_sha256":"35fa1f61ae88e5aab30044fabf33e90cd696fcd771e4fe101e031abe5355b456"},"schema_version":"1.0"},"canonical_sha256":"9fc64e20f7358c02823c2ad1c72849952455f4a72a8a019980ddd3f997c25c66","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:05.603369Z","signature_b64":"4uniFbSZ5s5e/KsfJ97kUbsPYBXfkDRq1RgZJukuCBo/JgzF26Ad+lAgZK6wfl4tGHoeG4jpRx0QM5PKmBv4Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9fc64e20f7358c02823c2ad1c72849952455f4a72a8a019980ddd3f997c25c66","last_reissued_at":"2026-05-17T23:44:05.602708Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:05.602708Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.01963","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tAsOx2YpzQnBUWycikqrJ0goB5Jq6gvqnsVJ/sxRhEwlzeZB+YI/hxOhBQemk3dxsTuhRDQbKKRBbJAnexw/AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T13:21:22.612783Z"},"content_sha256":"8c25ba153ac9d826660d378dd4cfb06b2d60a22a703bfa56ebe5e463f3620aa8","schema_version":"1.0","event_id":"sha256:8c25ba153ac9d826660d378dd4cfb06b2d60a22a703bfa56ebe5e463f3620aa8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:T7DE4IHXGWGAFAR4FLI4OKCJSU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Grounded Human-Object Interaction Hotspots from Video (Extended Abstract)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christoph Feichtenhofer, Kristen Grauman, Tushar Nagarajan","submitted_at":"2019-06-03T19:12:55Z","abstract_excerpt":"Learning how to interact with objects is an important step towards embodied visual intelligence, but existing techniques suffer from heavy supervision or sensing requirements. We propose an approach to learn human-object interaction \"hotspots\" directly from video. Rather than treat affordances as a manually supervised semantic segmentation task, our approach learns about interactions by watching videos of real human behavior and anticipating afforded actions. Given a novel image or video, our model infers a spatial hotspot map indicating how an object would be manipulated in a potential intera"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.01963","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":""},"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":"2026-05-17T23:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"20yckX70qnJQ42JOer0j41aWgBhiAzgj9GboiDNvBXAo2NRB9bgTBR0dKSzFODipUrvBq7/43wQ1VnCJiH6zCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T13:21:22.613452Z"},"content_sha256":"cac7884a7d3609475e2b0cf8ba28c3cf3e5c6f8a197bfb5d26ed4854dce7fb21","schema_version":"1.0","event_id":"sha256:cac7884a7d3609475e2b0cf8ba28c3cf3e5c6f8a197bfb5d26ed4854dce7fb21"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T7DE4IHXGWGAFAR4FLI4OKCJSU/bundle.json","state_url":"https://pith.science/pith/T7DE4IHXGWGAFAR4FLI4OKCJSU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T7DE4IHXGWGAFAR4FLI4OKCJSU/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":"2026-06-06T13:21:22Z","links":{"resolver":"https://pith.science/pith/T7DE4IHXGWGAFAR4FLI4OKCJSU","bundle":"https://pith.science/pith/T7DE4IHXGWGAFAR4FLI4OKCJSU/bundle.json","state":"https://pith.science/pith/T7DE4IHXGWGAFAR4FLI4OKCJSU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T7DE4IHXGWGAFAR4FLI4OKCJSU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:T7DE4IHXGWGAFAR4FLI4OKCJSU","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":"35fa1f61ae88e5aab30044fabf33e90cd696fcd771e4fe101e031abe5355b456","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-03T19:12:55Z","title_canon_sha256":"a16fe0c7059eabe3f883c8d998a7e6b2c782056369cbd377eef9a12a2f9e1948"},"schema_version":"1.0","source":{"id":"1906.01963","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.01963","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"1906.01963v1","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.01963","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"T7DE4IHXGWGA","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"T7DE4IHXGWGAFAR4","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"T7DE4IHX","created_at":"2026-05-18T12:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:cac7884a7d3609475e2b0cf8ba28c3cf3e5c6f8a197bfb5d26ed4854dce7fb21","target":"graph","created_at":"2026-05-17T23:44:05Z","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"},"paper":{"abstract_excerpt":"Learning how to interact with objects is an important step towards embodied visual intelligence, but existing techniques suffer from heavy supervision or sensing requirements. We propose an approach to learn human-object interaction \"hotspots\" directly from video. Rather than treat affordances as a manually supervised semantic segmentation task, our approach learns about interactions by watching videos of real human behavior and anticipating afforded actions. Given a novel image or video, our model infers a spatial hotspot map indicating how an object would be manipulated in a potential intera","authors_text":"Christoph Feichtenhofer, Kristen Grauman, Tushar Nagarajan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-03T19:12:55Z","title":"Grounded Human-Object Interaction Hotspots from Video (Extended Abstract)"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.01963","kind":"arxiv","version":1},"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":"sha256:8c25ba153ac9d826660d378dd4cfb06b2d60a22a703bfa56ebe5e463f3620aa8","target":"record","created_at":"2026-05-17T23:44:05Z","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":"35fa1f61ae88e5aab30044fabf33e90cd696fcd771e4fe101e031abe5355b456","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-03T19:12:55Z","title_canon_sha256":"a16fe0c7059eabe3f883c8d998a7e6b2c782056369cbd377eef9a12a2f9e1948"},"schema_version":"1.0","source":{"id":"1906.01963","kind":"arxiv","version":1}},"canonical_sha256":"9fc64e20f7358c02823c2ad1c72849952455f4a72a8a019980ddd3f997c25c66","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9fc64e20f7358c02823c2ad1c72849952455f4a72a8a019980ddd3f997c25c66","first_computed_at":"2026-05-17T23:44:05.602708Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:05.602708Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4uniFbSZ5s5e/KsfJ97kUbsPYBXfkDRq1RgZJukuCBo/JgzF26Ad+lAgZK6wfl4tGHoeG4jpRx0QM5PKmBv4Bg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:05.603369Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.01963","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8c25ba153ac9d826660d378dd4cfb06b2d60a22a703bfa56ebe5e463f3620aa8","sha256:cac7884a7d3609475e2b0cf8ba28c3cf3e5c6f8a197bfb5d26ed4854dce7fb21"],"state_sha256":"565bed29ab51d23b977c48e32e93ad6cc78e2d96ff8a5618b13933ab3c456a50"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OX8U3g8K796cAqgwd0dC7rFshhbKZy3lybl7ge7S1cZ94aMsUVyhb+gdeRqm5UgwPf98Kg3RnRUtaPGyhdK0Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T13:21:22.616450Z","bundle_sha256":"d0c0705b8d686c895f77732cd34131dc6d9a3534a37be10172ccaee99a137d53"}}