{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:5HPJV2Q4VE2HWDX24D2YPNU37O","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":"a9030f5911778a05616b51eaf164ebdbf84baeccb639f88bdcefd38ac1babc7b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-10-05T01:29:54Z","title_canon_sha256":"d675b047f815652d9a1b9b9a92dd4c2828d9eb1207c76a8218d9bd263c44f8a2"},"schema_version":"1.0","source":{"id":"1910.02190","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.02190","created_at":"2026-07-05T00:10:55Z"},{"alias_kind":"arxiv_version","alias_value":"1910.02190v2","created_at":"2026-07-05T00:10:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.02190","created_at":"2026-07-05T00:10:55Z"},{"alias_kind":"pith_short_12","alias_value":"5HPJV2Q4VE2H","created_at":"2026-07-05T00:10:55Z"},{"alias_kind":"pith_short_16","alias_value":"5HPJV2Q4VE2HWDX2","created_at":"2026-07-05T00:10:55Z"},{"alias_kind":"pith_short_8","alias_value":"5HPJV2Q4","created_at":"2026-07-05T00:10:55Z"}],"graph_snapshots":[{"event_id":"sha256:db114e0537e5d74470b5ce1282d4511a69573249f98b2cae2ceeca3ec98e2b3d","target":"graph","created_at":"2026-07-05T00:10:55Z","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/1910.02190/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work presents Kornia -- an open source computer vision library which consists of a set of differentiable routines and modules to solve generic computer vision problems. The package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by OpenCV, Kornia is composed of a set of modules containing operators that can be inserted inside neural networks to train models to perform image transformations, camera calibration, epipolar geometry, and low level image processi","authors_text":"Daniel Ponsa, Dmytro Mishkin, Edgar Riba, Ethan Rublee, Gary Bradski","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-10-05T01:29:54Z","title":"Kornia: an Open Source Differentiable Computer Vision Library for PyTorch"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.02190","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":"sha256:654d14eeccce3f334372588e6e9e2c33ebbbc8433fefebacb8447b7a08c25234","target":"record","created_at":"2026-07-05T00:10:55Z","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":"a9030f5911778a05616b51eaf164ebdbf84baeccb639f88bdcefd38ac1babc7b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-10-05T01:29:54Z","title_canon_sha256":"d675b047f815652d9a1b9b9a92dd4c2828d9eb1207c76a8218d9bd263c44f8a2"},"schema_version":"1.0","source":{"id":"1910.02190","kind":"arxiv","version":2}},"canonical_sha256":"e9de9aea1ca9347b0efae0f587b69bfb8ddac9f3a64a15a69bc8134d45f12ce6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e9de9aea1ca9347b0efae0f587b69bfb8ddac9f3a64a15a69bc8134d45f12ce6","first_computed_at":"2026-07-05T00:10:55.094289Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:10:55.094289Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RboiZtXF3FuKuHyWqfSL/f7IrlDmoOX4iZic2kswuCLtzDNDVHjQJi6luUZSlXZZ7MWZQx4S6HlCPpvo8lTPDA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:10:55.094686Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.02190","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:654d14eeccce3f334372588e6e9e2c33ebbbc8433fefebacb8447b7a08c25234","sha256:db114e0537e5d74470b5ce1282d4511a69573249f98b2cae2ceeca3ec98e2b3d"],"state_sha256":"9474415accdac62a6a764c54e5c8745a6b717150e32c4548d04746b6d8684345"}