{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:4DT2EF5MZ2ZOLY6727PKVOXWJN","short_pith_number":"pith:4DT2EF5M","canonical_record":{"source":{"id":"2104.11487","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-23T09:10:39Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c2089fd03a634aa1e70dcf070b0477840ab9a8f9b7e7967f4202e4509d58724b","abstract_canon_sha256":"df46bdcf98547b4c5ad62aa76fc88f75bab6653855aab4bd414537f9466be04c"},"schema_version":"1.0"},"canonical_sha256":"e0e7a217acceb2e5e3dfd7deaabaf64b787cae3dda58bf00e0c834d7293d3623","source":{"kind":"arxiv","id":"2104.11487","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.11487","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"arxiv_version","alias_value":"2104.11487v1","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.11487","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"pith_short_12","alias_value":"4DT2EF5MZ2ZO","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"pith_short_16","alias_value":"4DT2EF5MZ2ZOLY67","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"pith_short_8","alias_value":"4DT2EF5M","created_at":"2026-07-05T02:34:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:4DT2EF5MZ2ZOLY6727PKVOXWJN","target":"record","payload":{"canonical_record":{"source":{"id":"2104.11487","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-23T09:10:39Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c2089fd03a634aa1e70dcf070b0477840ab9a8f9b7e7967f4202e4509d58724b","abstract_canon_sha256":"df46bdcf98547b4c5ad62aa76fc88f75bab6653855aab4bd414537f9466be04c"},"schema_version":"1.0"},"canonical_sha256":"e0e7a217acceb2e5e3dfd7deaabaf64b787cae3dda58bf00e0c834d7293d3623","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:34:32.483968Z","signature_b64":"gP/oTmpcFmD19VQpNrdrpf4mcNBnyNTb6hf8d9fqPgBbMa7+7mz6uQp5lgI+ttNEsHZp+cCl/nQ7iGCGJ/XcDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e0e7a217acceb2e5e3dfd7deaabaf64b787cae3dda58bf00e0c834d7293d3623","last_reissued_at":"2026-07-05T02:34:32.483437Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:34:32.483437Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.11487","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":"2026-07-05T02:34:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5JT/mKtIFZ2HNeCCIY9BKOHjrNO/HvmapjcvCWDMq8PTD5XJ/9VOBQGgn8gZ+soSPTrzgvvn8lxmETK8evlaDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:02:36.616419Z"},"content_sha256":"8e08eba00a9a0a688c85b992e91acaa3993a76a576b0cd1c19f5b64e40a37acc","schema_version":"1.0","event_id":"sha256:8e08eba00a9a0a688c85b992e91acaa3993a76a576b0cd1c19f5b64e40a37acc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:4DT2EF5MZ2ZOLY6727PKVOXWJN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Skip-Convolutions for Efficient Video Processing","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Amirhossein Habibian, Babak Ehteshami Bejnordi, Davide Abati, Taco S. Cohen","submitted_at":"2021-04-23T09:10:39Z","abstract_excerpt":"We propose Skip-Convolutions to leverage the large amount of redundancies in video streams and save computations. Each video is represented as a series of changes across frames and network activations, denoted as residuals. We reformulate standard convolution to be efficiently computed on residual frames: each layer is coupled with a binary gate deciding whether a residual is important to the model prediction,~\\eg foreground regions, or it can be safely skipped, e.g. background regions. These gates can either be implemented as an efficient network trained jointly with convolution kernels, or c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.11487","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2104.11487/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":"2026-07-05T02:34:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lZCZQzr9JRPkuiS+7N3JHqz8amnYXLs0VB8Eul2pMwvUIFXQFFTg8Ifdjm8PP8uJAAN6BfuzihaKIoFYUQlGBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:02:36.617368Z"},"content_sha256":"4cd6740b7165910d46029ae690fa2fbda58b79daea483cbe7384cac63a2c5223","schema_version":"1.0","event_id":"sha256:4cd6740b7165910d46029ae690fa2fbda58b79daea483cbe7384cac63a2c5223"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4DT2EF5MZ2ZOLY6727PKVOXWJN/bundle.json","state_url":"https://pith.science/pith/4DT2EF5MZ2ZOLY6727PKVOXWJN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4DT2EF5MZ2ZOLY6727PKVOXWJN/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":"2026-08-06T13:02:36Z","links":{"resolver":"https://pith.science/pith/4DT2EF5MZ2ZOLY6727PKVOXWJN","bundle":"https://pith.science/pith/4DT2EF5MZ2ZOLY6727PKVOXWJN/bundle.json","state":"https://pith.science/pith/4DT2EF5MZ2ZOLY6727PKVOXWJN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4DT2EF5MZ2ZOLY6727PKVOXWJN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:4DT2EF5MZ2ZOLY6727PKVOXWJN","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":"df46bdcf98547b4c5ad62aa76fc88f75bab6653855aab4bd414537f9466be04c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-23T09:10:39Z","title_canon_sha256":"c2089fd03a634aa1e70dcf070b0477840ab9a8f9b7e7967f4202e4509d58724b"},"schema_version":"1.0","source":{"id":"2104.11487","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.11487","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"arxiv_version","alias_value":"2104.11487v1","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.11487","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"pith_short_12","alias_value":"4DT2EF5MZ2ZO","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"pith_short_16","alias_value":"4DT2EF5MZ2ZOLY67","created_at":"2026-07-05T02:34:32Z"},{"alias_kind":"pith_short_8","alias_value":"4DT2EF5M","created_at":"2026-07-05T02:34:32Z"}],"graph_snapshots":[{"event_id":"sha256:4cd6740b7165910d46029ae690fa2fbda58b79daea483cbe7384cac63a2c5223","target":"graph","created_at":"2026-07-05T02:34:32Z","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/2104.11487/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose Skip-Convolutions to leverage the large amount of redundancies in video streams and save computations. Each video is represented as a series of changes across frames and network activations, denoted as residuals. We reformulate standard convolution to be efficiently computed on residual frames: each layer is coupled with a binary gate deciding whether a residual is important to the model prediction,~\\eg foreground regions, or it can be safely skipped, e.g. background regions. These gates can either be implemented as an efficient network trained jointly with convolution kernels, or c","authors_text":"Amirhossein Habibian, Babak Ehteshami Bejnordi, Davide Abati, Taco S. Cohen","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-23T09:10:39Z","title":"Skip-Convolutions for Efficient Video Processing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.11487","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":"sha256:8e08eba00a9a0a688c85b992e91acaa3993a76a576b0cd1c19f5b64e40a37acc","target":"record","created_at":"2026-07-05T02:34:32Z","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":"df46bdcf98547b4c5ad62aa76fc88f75bab6653855aab4bd414537f9466be04c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-23T09:10:39Z","title_canon_sha256":"c2089fd03a634aa1e70dcf070b0477840ab9a8f9b7e7967f4202e4509d58724b"},"schema_version":"1.0","source":{"id":"2104.11487","kind":"arxiv","version":1}},"canonical_sha256":"e0e7a217acceb2e5e3dfd7deaabaf64b787cae3dda58bf00e0c834d7293d3623","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0e7a217acceb2e5e3dfd7deaabaf64b787cae3dda58bf00e0c834d7293d3623","first_computed_at":"2026-07-05T02:34:32.483437Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:34:32.483437Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gP/oTmpcFmD19VQpNrdrpf4mcNBnyNTb6hf8d9fqPgBbMa7+7mz6uQp5lgI+ttNEsHZp+cCl/nQ7iGCGJ/XcDw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:34:32.483968Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.11487","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8e08eba00a9a0a688c85b992e91acaa3993a76a576b0cd1c19f5b64e40a37acc","sha256:4cd6740b7165910d46029ae690fa2fbda58b79daea483cbe7384cac63a2c5223"],"state_sha256":"d4d3e05c155d015d94ac859b5c3f8cc9f7f47d24746ab3f59fafd027afddfecb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FNUS9j3pMT0eKjSdG2ML+9Rv4IqSFQN5L73jijui8RLIgtw+Ccp8mfhyjLcnjnnlqvtOqhE47XNa7qSuzvFAAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T13:02:36.624337Z","bundle_sha256":"b86f5586f3ce4ce4349f0c5af65f738ea0de68e332536a9e7d4494ac01b4a5ef"}}