{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:UCMP53O53D2NFII67BGSUMLBRS","short_pith_number":"pith:UCMP53O5","schema_version":"1.0","canonical_sha256":"a098feedddd8f4d2a11ef84d2a31618cb1264edd7c7397dd602aa011e85a112e","source":{"kind":"arxiv","id":"2008.09918","version":2},"attestation_state":"computed","paper":{"title":"Quantitative Survey of the State of the Art in Sign Language Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Oscar Koller","submitted_at":"2020-08-22T21:57:48Z","abstract_excerpt":"This work presents a meta study covering around 300 published sign language recognition papers with over 400 experimental results. It includes most papers between the start of the field in 1983 and 2020. Additionally, it covers a fine-grained analysis on over 25 studies that have compared their recognition approaches on RWTH-PHOENIX-Weather 2014, the standard benchmark task of the field. Research in the domain of sign language recognition has progressed significantly in the last decade, reaching a point where the task attracts much more attention than ever before. This study compiles the state"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2008.09918","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-22T21:57:48Z","cross_cats_sorted":[],"title_canon_sha256":"4c60655d114476a07762a010831a7ce72b4cfb3f09aa836ad4d70fd0d47ae7a4","abstract_canon_sha256":"f7a83c1b36a690a27a2f38ee46c695689fc5336604899229c2af92c71f3e64c4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:31:30.540936Z","signature_b64":"jt7O2yR3stcZVYePiXY8lhQhDr2q8B3TZAUd3vTj+qiAoihUPlf9UC5VhDrETUw2s0wkoJa5pbHBfbK5kzB5Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a098feedddd8f4d2a11ef84d2a31618cb1264edd7c7397dd602aa011e85a112e","last_reissued_at":"2026-07-05T01:31:30.540573Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:31:30.540573Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Quantitative Survey of the State of the Art in Sign Language Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Oscar Koller","submitted_at":"2020-08-22T21:57:48Z","abstract_excerpt":"This work presents a meta study covering around 300 published sign language recognition papers with over 400 experimental results. It includes most papers between the start of the field in 1983 and 2020. Additionally, it covers a fine-grained analysis on over 25 studies that have compared their recognition approaches on RWTH-PHOENIX-Weather 2014, the standard benchmark task of the field. Research in the domain of sign language recognition has progressed significantly in the last decade, reaching a point where the task attracts much more attention than ever before. This study compiles the state"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.09918","kind":"arxiv","version":2},"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/2008.09918/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2008.09918","created_at":"2026-07-05T01:31:30.540635+00:00"},{"alias_kind":"arxiv_version","alias_value":"2008.09918v2","created_at":"2026-07-05T01:31:30.540635+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.09918","created_at":"2026-07-05T01:31:30.540635+00:00"},{"alias_kind":"pith_short_12","alias_value":"UCMP53O53D2N","created_at":"2026-07-05T01:31:30.540635+00:00"},{"alias_kind":"pith_short_16","alias_value":"UCMP53O53D2NFII6","created_at":"2026-07-05T01:31:30.540635+00:00"},{"alias_kind":"pith_short_8","alias_value":"UCMP53O5","created_at":"2026-07-05T01:31:30.540635+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":4,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.23328","citing_title":"Emotion Recognition in Sign Language Conversation","ref_index":4,"is_internal_anchor":false},{"citing_arxiv_id":"2605.06351","citing_title":"SIGMA-ASL: Sensor-Integrated Multimodal Dataset for Sign Language Recognition","ref_index":44,"is_internal_anchor":false},{"citing_arxiv_id":"2605.01720","citing_title":"SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 55+ Sign Languages","ref_index":8,"is_internal_anchor":false},{"citing_arxiv_id":"2604.10106","citing_title":"VGGT-HPE: Reframing Head Pose Estimation as Relative Pose Prediction","ref_index":20,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS","json":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS.json","graph_json":"https://pith.science/api/pith-number/UCMP53O53D2NFII67BGSUMLBRS/graph.json","events_json":"https://pith.science/api/pith-number/UCMP53O53D2NFII67BGSUMLBRS/events.json","paper":"https://pith.science/paper/UCMP53O5"},"agent_actions":{"view_html":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS","download_json":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS.json","view_paper":"https://pith.science/paper/UCMP53O5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2008.09918&json=true","fetch_graph":"https://pith.science/api/pith-number/UCMP53O53D2NFII67BGSUMLBRS/graph.json","fetch_events":"https://pith.science/api/pith-number/UCMP53O53D2NFII67BGSUMLBRS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS/action/storage_attestation","attest_author":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS/action/author_attestation","sign_citation":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS/action/citation_signature","submit_replication":"https://pith.science/pith/UCMP53O53D2NFII67BGSUMLBRS/action/replication_record"}},"created_at":"2026-07-05T01:31:30.540635+00:00","updated_at":"2026-07-05T01:31:30.540635+00:00"}