{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:3CIDSYNKZUB627OCO6SWCMYJXE","short_pith_number":"pith:3CIDSYNK","canonical_record":{"source":{"id":"2003.11540","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-25T17:58:43Z","cross_cats_sorted":[],"title_canon_sha256":"00444d95cadc35bd161377c6b22a424cd941555d2b99e2e0fed63bee89d0d487","abstract_canon_sha256":"0db2d5a195408a0d8e47f85616a0e5de0831ddbd0085c24fbc93c786e15c9fe5"},"schema_version":"1.0"},"canonical_sha256":"d8903961aacd03ed7dc277a5613309b920e0c8eed5885e64d932e1f3c7ae0b5c","source":{"kind":"arxiv","id":"2003.11540","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.11540","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"arxiv_version","alias_value":"2003.11540v2","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.11540","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"pith_short_12","alias_value":"3CIDSYNKZUB6","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"pith_short_16","alias_value":"3CIDSYNKZUB627OC","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"pith_short_8","alias_value":"3CIDSYNK","created_at":"2026-07-05T00:59:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:3CIDSYNKZUB627OCO6SWCMYJXE","target":"record","payload":{"canonical_record":{"source":{"id":"2003.11540","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-25T17:58:43Z","cross_cats_sorted":[],"title_canon_sha256":"00444d95cadc35bd161377c6b22a424cd941555d2b99e2e0fed63bee89d0d487","abstract_canon_sha256":"0db2d5a195408a0d8e47f85616a0e5de0831ddbd0085c24fbc93c786e15c9fe5"},"schema_version":"1.0"},"canonical_sha256":"d8903961aacd03ed7dc277a5613309b920e0c8eed5885e64d932e1f3c7ae0b5c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:59:35.980559Z","signature_b64":"BuXzuhIG5U0PnxGBMYkjsXaxLIIYaYGbE/wtO+eF7I+YExrcfgdoK2r1ZvkG49+S7j18HN0wcuiZEG5SUZvGDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d8903961aacd03ed7dc277a5613309b920e0c8eed5885e64d932e1f3c7ae0b5c","last_reissued_at":"2026-07-05T00:59:35.980098Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:59:35.980098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2003.11540","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":"2026-07-05T00:59:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jda+xQfiBViywCJXjRt4gkiVJR94923+gRtVegzxhosExms2s4Y0I2sGOsfI0k1Yz4alhRiO7DlkipFwvW0/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:53:43.283453Z"},"content_sha256":"e11a050f882c5d94cc9cc544886779d755b804133f613d79ee155b54e566f264","schema_version":"1.0","event_id":"sha256:e11a050f882c5d94cc9cc544886779d755b804133f613d79ee155b54e566f264"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:3CIDSYNKZUB627OCO6SWCMYJXE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning What to Learn for Video Object Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andreas Robinson, Felix J\\\"aremo Lawin, Goutam Bhat, Luc Van Gool, Martin Danelljan, Michael Felsberg, Radu Timofte","submitted_at":"2020-03-25T17:58:43Z","abstract_excerpt":"Video object segmentation (VOS) is a highly challenging problem, since the target object is only defined during inference with a given first-frame reference mask. The problem of how to capture and utilize this limited target information remains a fundamental research question. We address this by introducing an end-to-end trainable VOS architecture that integrates a differentiable few-shot learning module. This internal learner is designed to predict a powerful parametric model of the target by minimizing a segmentation error in the first frame. We further go beyond standard few-shot learning t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.11540","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/2003.11540/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":"2026-07-05T00:59:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z2aOaug89FHOAk62lHjE6DJI5e5rWZvBebO5RZAbJNUiQy9mnwKNcYBL4EtPsuwXVahpVDwpqSQLWUgv2hPLCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:53:43.283827Z"},"content_sha256":"8bc63d16d283ea34b4d5884707501a902d6cbc3e28a058f70a8c3103f731fa16","schema_version":"1.0","event_id":"sha256:8bc63d16d283ea34b4d5884707501a902d6cbc3e28a058f70a8c3103f731fa16"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3CIDSYNKZUB627OCO6SWCMYJXE/bundle.json","state_url":"https://pith.science/pith/3CIDSYNKZUB627OCO6SWCMYJXE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3CIDSYNKZUB627OCO6SWCMYJXE/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":"2026-07-06T16:53:43Z","links":{"resolver":"https://pith.science/pith/3CIDSYNKZUB627OCO6SWCMYJXE","bundle":"https://pith.science/pith/3CIDSYNKZUB627OCO6SWCMYJXE/bundle.json","state":"https://pith.science/pith/3CIDSYNKZUB627OCO6SWCMYJXE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3CIDSYNKZUB627OCO6SWCMYJXE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:3CIDSYNKZUB627OCO6SWCMYJXE","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":"0db2d5a195408a0d8e47f85616a0e5de0831ddbd0085c24fbc93c786e15c9fe5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-25T17:58:43Z","title_canon_sha256":"00444d95cadc35bd161377c6b22a424cd941555d2b99e2e0fed63bee89d0d487"},"schema_version":"1.0","source":{"id":"2003.11540","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.11540","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"arxiv_version","alias_value":"2003.11540v2","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.11540","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"pith_short_12","alias_value":"3CIDSYNKZUB6","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"pith_short_16","alias_value":"3CIDSYNKZUB627OC","created_at":"2026-07-05T00:59:35Z"},{"alias_kind":"pith_short_8","alias_value":"3CIDSYNK","created_at":"2026-07-05T00:59:35Z"}],"graph_snapshots":[{"event_id":"sha256:8bc63d16d283ea34b4d5884707501a902d6cbc3e28a058f70a8c3103f731fa16","target":"graph","created_at":"2026-07-05T00:59:35Z","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/2003.11540/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Video object segmentation (VOS) is a highly challenging problem, since the target object is only defined during inference with a given first-frame reference mask. The problem of how to capture and utilize this limited target information remains a fundamental research question. We address this by introducing an end-to-end trainable VOS architecture that integrates a differentiable few-shot learning module. This internal learner is designed to predict a powerful parametric model of the target by minimizing a segmentation error in the first frame. We further go beyond standard few-shot learning t","authors_text":"Andreas Robinson, Felix J\\\"aremo Lawin, Goutam Bhat, Luc Van Gool, Martin Danelljan, Michael Felsberg, Radu Timofte","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-25T17:58:43Z","title":"Learning What to Learn for Video Object Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.11540","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:e11a050f882c5d94cc9cc544886779d755b804133f613d79ee155b54e566f264","target":"record","created_at":"2026-07-05T00:59:35Z","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":"0db2d5a195408a0d8e47f85616a0e5de0831ddbd0085c24fbc93c786e15c9fe5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-25T17:58:43Z","title_canon_sha256":"00444d95cadc35bd161377c6b22a424cd941555d2b99e2e0fed63bee89d0d487"},"schema_version":"1.0","source":{"id":"2003.11540","kind":"arxiv","version":2}},"canonical_sha256":"d8903961aacd03ed7dc277a5613309b920e0c8eed5885e64d932e1f3c7ae0b5c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d8903961aacd03ed7dc277a5613309b920e0c8eed5885e64d932e1f3c7ae0b5c","first_computed_at":"2026-07-05T00:59:35.980098Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:59:35.980098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BuXzuhIG5U0PnxGBMYkjsXaxLIIYaYGbE/wtO+eF7I+YExrcfgdoK2r1ZvkG49+S7j18HN0wcuiZEG5SUZvGDw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:59:35.980559Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.11540","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e11a050f882c5d94cc9cc544886779d755b804133f613d79ee155b54e566f264","sha256:8bc63d16d283ea34b4d5884707501a902d6cbc3e28a058f70a8c3103f731fa16"],"state_sha256":"664b1eea883aced101b384ed37d9d99798cf20914bf80c4812a71e501f0189a6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YwXJSqgo/n2VdSR1EbANB+vNTH+fcju5EHL1qjSPB2PPlZc3rWf4TS0BucrlPWZx+SUon44Mo1xFY20NtbYtBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T16:53:43.285821Z","bundle_sha256":"9e21585c016613f7380b59da2f0dfb6e78347310bada128e931302cad77ad38e"}}