{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:C6ZBMIH4JJD2WPJTBXLWS4HIZM","short_pith_number":"pith:C6ZBMIH4","canonical_record":{"source":{"id":"2102.04530","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-02-08T21:04:21Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"58b2310e6ba4babe0dde5e80aaed3da84723e55aa5b0bc4f8ecd68bed9088c21","abstract_canon_sha256":"22bd562fc6f1a42e27685f1549a48e7fe146517d81f4225f71d07245ac4e527d"},"schema_version":"1.0"},"canonical_sha256":"17b21620fc4a47ab3d330dd76970e8cb31b0e1915e8f48c2d066c2e33cf05364","source":{"kind":"arxiv","id":"2102.04530","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.04530","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"arxiv_version","alias_value":"2102.04530v1","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.04530","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_12","alias_value":"C6ZBMIH4JJD2","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_16","alias_value":"C6ZBMIH4JJD2WPJT","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_8","alias_value":"C6ZBMIH4","created_at":"2026-07-05T02:13:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:C6ZBMIH4JJD2WPJTBXLWS4HIZM","target":"record","payload":{"canonical_record":{"source":{"id":"2102.04530","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-02-08T21:04:21Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"58b2310e6ba4babe0dde5e80aaed3da84723e55aa5b0bc4f8ecd68bed9088c21","abstract_canon_sha256":"22bd562fc6f1a42e27685f1549a48e7fe146517d81f4225f71d07245ac4e527d"},"schema_version":"1.0"},"canonical_sha256":"17b21620fc4a47ab3d330dd76970e8cb31b0e1915e8f48c2d066c2e33cf05364","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:13:34.865792Z","signature_b64":"MYUdD+UjT8deNBq5yqpViRsbn3SUwg1SA3//70P/aIMnH1DZaZQygqTkrLN5fdC9WDTZ7rgTALomq+kgl4E9Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17b21620fc4a47ab3d330dd76970e8cb31b0e1915e8f48c2d066c2e33cf05364","last_reissued_at":"2026-07-05T02:13:34.865362Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:13:34.865362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2102.04530","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":"2026-07-05T02:13:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0r41lowKvzv4WLC2yL2EnRGr46hIsIpqMapLX+EAAcRON+stOv9uApmlGgVK9ecqXb3ExVUQA+wQti/x1aDnBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T10:47:55.390530Z"},"content_sha256":"cadb9dd3de5f269f977f80bf661f4775a583b4ab9289517fe3d117bc33d40bd3","schema_version":"1.0","event_id":"sha256:cadb9dd3de5f269f977f80bf661f4775a583b4ab9289517fe3d117bc33d40bd3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:C6ZBMIH4JJD2WPJTBXLWS4HIZM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.RO"],"primary_cat":"cs.CV","authors_text":"Bingbing Liu, Ehsan Taghavi, Enxu Li, Ran Cheng, Ryan Razani","submitted_at":"2021-02-08T21:04:21Z","abstract_excerpt":"Autonomous robotic systems and self driving cars rely on accurate perception of their surroundings as the safety of the passengers and pedestrians is the top priority. Semantic segmentation is one the essential components of environmental perception that provides semantic information of the scene. Recently, several methods have been introduced for 3D LiDAR semantic segmentation. While, they can lead to improved performance, they are either afflicted by high computational complexity, therefore are inefficient, or lack fine details of smaller instances. To alleviate this problem, we propose AF2-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.04530","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/2102.04530/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":"2026-07-05T02:13:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JCvxsOUfbRl0/v6Gmku5EAW6djCNX9Jo26RbS6zJXjeOLAQRH+y1rnISVFfucjQ5437fBMML1mzI7r7JUrMCBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T10:47:55.390980Z"},"content_sha256":"96b4a935fd6a6368b67e509553686dd8321f1d3f7a6678f5e6a9ecd187019ee5","schema_version":"1.0","event_id":"sha256:96b4a935fd6a6368b67e509553686dd8321f1d3f7a6678f5e6a9ecd187019ee5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C6ZBMIH4JJD2WPJTBXLWS4HIZM/bundle.json","state_url":"https://pith.science/pith/C6ZBMIH4JJD2WPJTBXLWS4HIZM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C6ZBMIH4JJD2WPJTBXLWS4HIZM/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":"2026-07-05T10:47:55Z","links":{"resolver":"https://pith.science/pith/C6ZBMIH4JJD2WPJTBXLWS4HIZM","bundle":"https://pith.science/pith/C6ZBMIH4JJD2WPJTBXLWS4HIZM/bundle.json","state":"https://pith.science/pith/C6ZBMIH4JJD2WPJTBXLWS4HIZM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C6ZBMIH4JJD2WPJTBXLWS4HIZM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:C6ZBMIH4JJD2WPJTBXLWS4HIZM","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":"22bd562fc6f1a42e27685f1549a48e7fe146517d81f4225f71d07245ac4e527d","cross_cats_sorted":["cs.AI","cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-02-08T21:04:21Z","title_canon_sha256":"58b2310e6ba4babe0dde5e80aaed3da84723e55aa5b0bc4f8ecd68bed9088c21"},"schema_version":"1.0","source":{"id":"2102.04530","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.04530","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"arxiv_version","alias_value":"2102.04530v1","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.04530","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_12","alias_value":"C6ZBMIH4JJD2","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_16","alias_value":"C6ZBMIH4JJD2WPJT","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_8","alias_value":"C6ZBMIH4","created_at":"2026-07-05T02:13:34Z"}],"graph_snapshots":[{"event_id":"sha256:96b4a935fd6a6368b67e509553686dd8321f1d3f7a6678f5e6a9ecd187019ee5","target":"graph","created_at":"2026-07-05T02:13:34Z","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/2102.04530/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Autonomous robotic systems and self driving cars rely on accurate perception of their surroundings as the safety of the passengers and pedestrians is the top priority. Semantic segmentation is one the essential components of environmental perception that provides semantic information of the scene. Recently, several methods have been introduced for 3D LiDAR semantic segmentation. While, they can lead to improved performance, they are either afflicted by high computational complexity, therefore are inefficient, or lack fine details of smaller instances. To alleviate this problem, we propose AF2-","authors_text":"Bingbing Liu, Ehsan Taghavi, Enxu Li, Ran Cheng, Ryan Razani","cross_cats":["cs.AI","cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-02-08T21:04:21Z","title":"(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.04530","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:cadb9dd3de5f269f977f80bf661f4775a583b4ab9289517fe3d117bc33d40bd3","target":"record","created_at":"2026-07-05T02:13:34Z","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":"22bd562fc6f1a42e27685f1549a48e7fe146517d81f4225f71d07245ac4e527d","cross_cats_sorted":["cs.AI","cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-02-08T21:04:21Z","title_canon_sha256":"58b2310e6ba4babe0dde5e80aaed3da84723e55aa5b0bc4f8ecd68bed9088c21"},"schema_version":"1.0","source":{"id":"2102.04530","kind":"arxiv","version":1}},"canonical_sha256":"17b21620fc4a47ab3d330dd76970e8cb31b0e1915e8f48c2d066c2e33cf05364","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17b21620fc4a47ab3d330dd76970e8cb31b0e1915e8f48c2d066c2e33cf05364","first_computed_at":"2026-07-05T02:13:34.865362Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:13:34.865362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MYUdD+UjT8deNBq5yqpViRsbn3SUwg1SA3//70P/aIMnH1DZaZQygqTkrLN5fdC9WDTZ7rgTALomq+kgl4E9Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:13:34.865792Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.04530","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cadb9dd3de5f269f977f80bf661f4775a583b4ab9289517fe3d117bc33d40bd3","sha256:96b4a935fd6a6368b67e509553686dd8321f1d3f7a6678f5e6a9ecd187019ee5"],"state_sha256":"5268de0dbd38a72067d598374e24e09187043d955993121f7b45d325a067752c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p03xm4KX7S+3cYKfimObHfshYa9cNUjVWrQnZWKlHzQd6a1B3fCcAqbzQ62GDupjWetLSUvp8rxVFhOcOWG/CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T10:47:55.393411Z","bundle_sha256":"dcfd1224157894bacca7e25eb46076da00fc9ab3eacad9103fab541e989d1876"}}