{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:IQFT5C5ZGGMVTPVZZ5NHAQPU6Z","short_pith_number":"pith:IQFT5C5Z","schema_version":"1.0","canonical_sha256":"440b3e8bb9319959beb9cf5a7041f4f673d00e61b1fb596ce9b9cff464ddc62b","source":{"kind":"arxiv","id":"1604.05933","version":1},"attestation_state":"computed","paper":{"title":"Parametric Object Motion from Blur","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anita Sellent, Jochen Gast, Stefan Roth","submitted_at":"2016-04-20T13:00:30Z","abstract_excerpt":"Motion blur can adversely affect a number of vision tasks, hence it is generally considered a nuisance. We instead treat motion blur as a useful signal that allows to compute the motion of objects from a single image. Drawing on the success of joint segmentation and parametric motion models in the context of optical flow estimation, we propose a parametric object motion model combined with a segmentation mask to exploit localized, non-uniform motion blur. Our parametric image formation model is differentiable w.r.t. the motion parameters, which enables us to generalize marginal-likelihood tech"},"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":"1604.05933","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-20T13:00:30Z","cross_cats_sorted":[],"title_canon_sha256":"2b19503661970d078050e9758f9c95153c3d77c5239e98c2f06fc0c02964afcd","abstract_canon_sha256":"bf5b472c8467ed552a144207b7b0bf659e3dce8a021636349089fcd6e36f23bd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:16:34.191057Z","signature_b64":"Xfbj2O9mTeGQuDKmfdk98iqfcRXKRpXW7N9kV1eIHp8Ou+WNcsZ3+RBsNX4RVdzXKt868Vhept8yipNfaKENAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"440b3e8bb9319959beb9cf5a7041f4f673d00e61b1fb596ce9b9cff464ddc62b","last_reissued_at":"2026-05-18T01:16:34.190290Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:16:34.190290Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Parametric Object Motion from Blur","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anita Sellent, Jochen Gast, Stefan Roth","submitted_at":"2016-04-20T13:00:30Z","abstract_excerpt":"Motion blur can adversely affect a number of vision tasks, hence it is generally considered a nuisance. We instead treat motion blur as a useful signal that allows to compute the motion of objects from a single image. Drawing on the success of joint segmentation and parametric motion models in the context of optical flow estimation, we propose a parametric object motion model combined with a segmentation mask to exploit localized, non-uniform motion blur. Our parametric image formation model is differentiable w.r.t. the motion parameters, which enables us to generalize marginal-likelihood tech"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.05933","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1604.05933","created_at":"2026-05-18T01:16:34.190427+00:00"},{"alias_kind":"arxiv_version","alias_value":"1604.05933v1","created_at":"2026-05-18T01:16:34.190427+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.05933","created_at":"2026-05-18T01:16:34.190427+00:00"},{"alias_kind":"pith_short_12","alias_value":"IQFT5C5ZGGMV","created_at":"2026-05-18T12:30:22.444734+00:00"},{"alias_kind":"pith_short_16","alias_value":"IQFT5C5ZGGMVTPVZ","created_at":"2026-05-18T12:30:22.444734+00:00"},{"alias_kind":"pith_short_8","alias_value":"IQFT5C5Z","created_at":"2026-05-18T12:30:22.444734+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/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z","json":"https://pith.science/pith/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z.json","graph_json":"https://pith.science/api/pith-number/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/graph.json","events_json":"https://pith.science/api/pith-number/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/events.json","paper":"https://pith.science/paper/IQFT5C5Z"},"agent_actions":{"view_html":"https://pith.science/pith/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z","download_json":"https://pith.science/pith/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z.json","view_paper":"https://pith.science/paper/IQFT5C5Z","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1604.05933&json=true","fetch_graph":"https://pith.science/api/pith-number/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/graph.json","fetch_events":"https://pith.science/api/pith-number/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/action/storage_attestation","attest_author":"https://pith.science/pith/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/action/author_attestation","sign_citation":"https://pith.science/pith/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/action/citation_signature","submit_replication":"https://pith.science/pith/IQFT5C5ZGGMVTPVZZ5NHAQPU6Z/action/replication_record"}},"created_at":"2026-05-18T01:16:34.190427+00:00","updated_at":"2026-05-18T01:16:34.190427+00:00"}