{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:WBFKLEK43E2ZIIUZH47575RL5E","short_pith_number":"pith:WBFKLEK4","canonical_record":{"source":{"id":"2011.02265","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-04T13:09:26Z","cross_cats_sorted":[],"title_canon_sha256":"4ff5f98cb5f27021475d9a1c8554c941cfff50507d613680d73259130f9ffba1","abstract_canon_sha256":"cd07df28f72d60b3af54754f2a7295081f847f386ebae876fd86db3dc70e8b35"},"schema_version":"1.0"},"canonical_sha256":"b04aa5915cd9359422993f3fdff62be924e339a41514f27a51932ca33439e01d","source":{"kind":"arxiv","id":"2011.02265","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.02265","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"arxiv_version","alias_value":"2011.02265v1","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.02265","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"pith_short_12","alias_value":"WBFKLEK43E2Z","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"pith_short_16","alias_value":"WBFKLEK43E2ZIIUZ","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"pith_short_8","alias_value":"WBFKLEK4","created_at":"2026-07-05T01:49:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:WBFKLEK43E2ZIIUZH47575RL5E","target":"record","payload":{"canonical_record":{"source":{"id":"2011.02265","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-04T13:09:26Z","cross_cats_sorted":[],"title_canon_sha256":"4ff5f98cb5f27021475d9a1c8554c941cfff50507d613680d73259130f9ffba1","abstract_canon_sha256":"cd07df28f72d60b3af54754f2a7295081f847f386ebae876fd86db3dc70e8b35"},"schema_version":"1.0"},"canonical_sha256":"b04aa5915cd9359422993f3fdff62be924e339a41514f27a51932ca33439e01d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:49:11.052693Z","signature_b64":"yOSTENGWhoiFF0lhEvgvr0LFAbxTJTcBnQNkVkMqNHq9aVxgs3dBt9Gqz1S3e3S8Zj0nQ/Wp38oj4m+ou1tlDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b04aa5915cd9359422993f3fdff62be924e339a41514f27a51932ca33439e01d","last_reissued_at":"2026-07-05T01:49:11.052276Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:49:11.052276Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.02265","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":"2026-07-05T01:49:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xufnJHDWUZEyO7qLUbrfG7m+7FerGpuzTpX1kOIe8DiR+VlOiOSoJvIbcLgWPNqOR3dYq/AiFNUM960cXq3dAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T23:54:41.274086Z"},"content_sha256":"5397352c0cb5b48c70b28718d5fc2ec1e1d40588ee9aaa50b370a8add4748afd","schema_version":"1.0","event_id":"sha256:5397352c0cb5b48c70b28718d5fc2ec1e1d40588ee9aaa50b370a8add4748afd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:WBFKLEK43E2ZIIUZH47575RL5E","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hai-Bao Chen, Hao Yu, Ngai Wong, Yuan Cheng, Yuchao Yang","submitted_at":"2020-11-04T13:09:26Z","abstract_excerpt":"Real-time understanding in video is crucial in various AI applications such as autonomous driving. This work presents a fast single-shot segmentation strategy for video scene understanding. The proposed net, called S3-Net, quickly locates and segments target sub-scenes, meanwhile extracts structured time-series semantic features as inputs to an LSTM-based spatio-temporal model. Utilizing tensorization and quantization techniques, S3-Net is intended to be lightweight for edge computing. Experiments using CityScapes, UCF11, HMDB51 and MOMENTS datasets demonstrate that the proposed S3-Net achieve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.02265","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/2011.02265/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":"2026-07-05T01:49:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zd6G6giLDrcGQitqp3jPlcnIPdsv7Mz8vGNIrDzeETAO+WMOaG0LQ4pXGVTlz19jB3jZnZU/tNU0p20rGrXACA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T23:54:41.274486Z"},"content_sha256":"7fc28478035334ddc5a75c87e91e41501c338c1d4d79bfd228b7d691dd4a4941","schema_version":"1.0","event_id":"sha256:7fc28478035334ddc5a75c87e91e41501c338c1d4d79bfd228b7d691dd4a4941"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WBFKLEK43E2ZIIUZH47575RL5E/bundle.json","state_url":"https://pith.science/pith/WBFKLEK43E2ZIIUZH47575RL5E/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WBFKLEK43E2ZIIUZH47575RL5E/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":"2026-07-08T23:54:41Z","links":{"resolver":"https://pith.science/pith/WBFKLEK43E2ZIIUZH47575RL5E","bundle":"https://pith.science/pith/WBFKLEK43E2ZIIUZH47575RL5E/bundle.json","state":"https://pith.science/pith/WBFKLEK43E2ZIIUZH47575RL5E/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WBFKLEK43E2ZIIUZH47575RL5E/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:WBFKLEK43E2ZIIUZH47575RL5E","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":"cd07df28f72d60b3af54754f2a7295081f847f386ebae876fd86db3dc70e8b35","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-04T13:09:26Z","title_canon_sha256":"4ff5f98cb5f27021475d9a1c8554c941cfff50507d613680d73259130f9ffba1"},"schema_version":"1.0","source":{"id":"2011.02265","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.02265","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"arxiv_version","alias_value":"2011.02265v1","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.02265","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"pith_short_12","alias_value":"WBFKLEK43E2Z","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"pith_short_16","alias_value":"WBFKLEK43E2ZIIUZ","created_at":"2026-07-05T01:49:11Z"},{"alias_kind":"pith_short_8","alias_value":"WBFKLEK4","created_at":"2026-07-05T01:49:11Z"}],"graph_snapshots":[{"event_id":"sha256:7fc28478035334ddc5a75c87e91e41501c338c1d4d79bfd228b7d691dd4a4941","target":"graph","created_at":"2026-07-05T01:49:11Z","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/2011.02265/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Real-time understanding in video is crucial in various AI applications such as autonomous driving. This work presents a fast single-shot segmentation strategy for video scene understanding. The proposed net, called S3-Net, quickly locates and segments target sub-scenes, meanwhile extracts structured time-series semantic features as inputs to an LSTM-based spatio-temporal model. Utilizing tensorization and quantization techniques, S3-Net is intended to be lightweight for edge computing. Experiments using CityScapes, UCF11, HMDB51 and MOMENTS datasets demonstrate that the proposed S3-Net achieve","authors_text":"Hai-Bao Chen, Hao Yu, Ngai Wong, Yuan Cheng, Yuchao Yang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-04T13:09:26Z","title":"S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.02265","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":"sha256:5397352c0cb5b48c70b28718d5fc2ec1e1d40588ee9aaa50b370a8add4748afd","target":"record","created_at":"2026-07-05T01:49:11Z","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":"cd07df28f72d60b3af54754f2a7295081f847f386ebae876fd86db3dc70e8b35","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-04T13:09:26Z","title_canon_sha256":"4ff5f98cb5f27021475d9a1c8554c941cfff50507d613680d73259130f9ffba1"},"schema_version":"1.0","source":{"id":"2011.02265","kind":"arxiv","version":1}},"canonical_sha256":"b04aa5915cd9359422993f3fdff62be924e339a41514f27a51932ca33439e01d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b04aa5915cd9359422993f3fdff62be924e339a41514f27a51932ca33439e01d","first_computed_at":"2026-07-05T01:49:11.052276Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:49:11.052276Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yOSTENGWhoiFF0lhEvgvr0LFAbxTJTcBnQNkVkMqNHq9aVxgs3dBt9Gqz1S3e3S8Zj0nQ/Wp38oj4m+ou1tlDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:49:11.052693Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.02265","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5397352c0cb5b48c70b28718d5fc2ec1e1d40588ee9aaa50b370a8add4748afd","sha256:7fc28478035334ddc5a75c87e91e41501c338c1d4d79bfd228b7d691dd4a4941"],"state_sha256":"481feeb75993af49d7ce3c3ce29963a809e2d583c9214328ac324d190f56eb5b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fo0NUofl3/6c5eTD8D89rUpr/VJ07TJijBFztKQSNCm2jUySqB0l1V7UnrexM56MR+51wpS/8xBJ6o4dPYzNBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T23:54:41.276478Z","bundle_sha256":"7e64f0fc0dfda2a672926703ad0ec382dd9a95451715e2b4a5c1a49c1681185d"}}