{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:76ETJ3T5D3SNF3QY6BFHJ45A6L","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":"a1e0daadecde461e6b3fc0a145b91ed0bd9691cb41af566781722c39bd3c52f0","cross_cats_sorted":["cs.LG","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-07T17:25:21Z","title_canon_sha256":"cc9022f4c48b19592d77fba85f67be318e43f31374c221ca39f8940471085f7e"},"schema_version":"1.0","source":{"id":"2003.03613","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.03613","created_at":"2026-07-05T00:50:28Z"},{"alias_kind":"arxiv_version","alias_value":"2003.03613v1","created_at":"2026-07-05T00:50:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.03613","created_at":"2026-07-05T00:50:28Z"},{"alias_kind":"pith_short_12","alias_value":"76ETJ3T5D3SN","created_at":"2026-07-05T00:50:28Z"},{"alias_kind":"pith_short_16","alias_value":"76ETJ3T5D3SNF3QY","created_at":"2026-07-05T00:50:28Z"},{"alias_kind":"pith_short_8","alias_value":"76ETJ3T5","created_at":"2026-07-05T00:50:28Z"}],"graph_snapshots":[{"event_id":"sha256:40a95f8899c6c2dbdb03bf3e29c33c4da7e62e48189e044e87d24efa8c4cde84","target":"graph","created_at":"2026-07-05T00:50:28Z","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/2003.03613/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we propose an end to end solution for image matting i.e high-precision extraction of foreground objects from natural images. Image matting and background detection can be achieved easily through chroma keying in a studio setting when the background is either pure green or blue. Nonetheless, image matting in natural scenes with complex and uneven depth backgrounds remains a tedious task that requires human intervention. To achieve complete automatic foreground extraction in natural scenes, we propose a method that assimilates semantic segmentation and deep image matting processes","authors_text":"Anirudha Vishvakarma, Rahul Deora, Rishab Sharma","cross_cats":["cs.LG","eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-07T17:25:21Z","title":"AlphaNet: An Attention Guided Deep Network for Automatic Image Matting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.03613","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":"sha256:53a8f268155ab958fe640eb0f919c91e7df6381f7ff062fed99d6be663bd6c46","target":"record","created_at":"2026-07-05T00:50:28Z","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":"a1e0daadecde461e6b3fc0a145b91ed0bd9691cb41af566781722c39bd3c52f0","cross_cats_sorted":["cs.LG","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-07T17:25:21Z","title_canon_sha256":"cc9022f4c48b19592d77fba85f67be318e43f31374c221ca39f8940471085f7e"},"schema_version":"1.0","source":{"id":"2003.03613","kind":"arxiv","version":1}},"canonical_sha256":"ff8934ee7d1ee4d2ee18f04a74f3a0f2eb00e919b6b88983259874717029d0ec","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff8934ee7d1ee4d2ee18f04a74f3a0f2eb00e919b6b88983259874717029d0ec","first_computed_at":"2026-07-05T00:50:28.507140Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:50:28.507140Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VPVWUaNY9j4k3q3zExeka8k5W75nmW6sUbVdLYzg3t1GZWQ7DRkoAMIV0J3uFCs1GyAG6Z7Pg+StlCedUaoMCg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:50:28.507518Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.03613","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:53a8f268155ab958fe640eb0f919c91e7df6381f7ff062fed99d6be663bd6c46","sha256:40a95f8899c6c2dbdb03bf3e29c33c4da7e62e48189e044e87d24efa8c4cde84"],"state_sha256":"370c54397b0267972c33d4b41ba9567f01c2eed3101a5846eff1e2057567f527"}