{"id":"https://openalex.org/W7138310485","doi":"https://doi.org/10.1609/aaai.v40i8.37607","title":"DTTNet: Improving Video Shadow Detection via Dark-Aware Guidance and Tokenized Temporal Modeling","display_name":"DTTNet: Improving Video Shadow Detection via Dark-Aware Guidance and Tokenized Temporal Modeling","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138310485","doi":"https://doi.org/10.1609/aaai.v40i8.37607"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i8.37607","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i8.37607","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i8.37607","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129670712","display_name":"Zhicheng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhicheng Li","raw_affiliation_strings":["China Unviersity of Mining and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Unviersity of Mining and Technology","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049765236","display_name":"Kunyang Sun","orcid":"https://orcid.org/0000-0002-5397-0735"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunyang Sun","raw_affiliation_strings":["China Unviersity of Mining and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Unviersity of Mining and Technology","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129686831","display_name":"Rui Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yao","raw_affiliation_strings":["China Unviersity of Mining and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Unviersity of Mining and Technology","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129706822","display_name":"Hancheng Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hancheng Zhu","raw_affiliation_strings":["China Unviersity of Mining and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Unviersity of Mining and Technology","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129752350","display_name":"Fuyuan Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I308837","display_name":"Suzhou University of Science and Technology","ror":"https://ror.org/04en8wb91","country_code":"CN","type":"education","lineage":["https://openalex.org/I308837"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuyuan Hu","raw_affiliation_strings":["Suzhou University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Suzhou University of Science and Technology","institution_ids":["https://openalex.org/I308837"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129670813","display_name":"Jiaqi Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Zhao","raw_affiliation_strings":["China Unviersity of Mining and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Unviersity of Mining and Technology","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081933126","display_name":"Zhiwen Shao","orcid":"https://orcid.org/0000-0002-9383-8384"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Shao","raw_affiliation_strings":["China Unviersity of Mining and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Unviersity of Mining and Technology","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129662025","display_name":"Yong Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Zhou","raw_affiliation_strings":["China Unviersity of Mining and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Unviersity of Mining and Technology","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"8","first_page":"6753","last_page":"6761"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.5098000168800354,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.5098000168800354,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.1145000010728836,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.1062999963760376,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/shadow","display_name":"Shadow (psychology)","score":0.6571000218391418},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5828999876976013},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4740999937057495},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4666999876499176},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4390000104904175},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4138999879360199},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3937999904155731},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.37369999289512634},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3709999918937683},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3698999881744385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7732999920845032},{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.6571000218391418},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6011999845504761},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5828999876976013},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5351999998092651},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4740999937057495},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4666999876499176},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4390000104904175},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3937999904155731},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.32350000739097595},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.3077999949455261},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C116544410","wikidata":"https://www.wikidata.org/wiki/Q1478122","display_name":"Shadow mapping","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.288100004196167},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2786000072956085},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25380000472068787},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.25}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i8.37607","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i8.37607","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/37607","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37607","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i8.37607","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i8.37607","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6156699657440186}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"shadow":[1,15,80,96],"detection":[2],"confronts":[3],"two":[4],"entwined":[5],"difficulties:":[6],"distinguishing":[7],"shadows":[8,47],"from":[9,48],"complex":[10],"backgrounds":[11],"and":[12,35,63,119],"modeling":[13,77],"dynamic":[14],"deformations":[16],"under":[17],"varying":[18],"illumination.":[19],"To":[20],"address":[21],"shadow-background":[22],"ambiguity,":[23],"we":[24,52,82],"leverage":[25],"linguistic":[26],"priors":[27],"through":[28],"the":[29,68],"proposed":[30],"Vision-language":[31],"Match":[32],"Module":[33],"(VMM)":[34],"a":[36,84],"Dark-aware":[37],"Semantic":[38],"Block":[39,87],"(DSB),":[40],"extracting":[41],"text-guided":[42],"features":[43],"to":[44,57],"explicitly":[45],"differentiate":[46],"dark":[49],"objects.":[50],"Furthermore,":[51],"introduce":[53],"adaptive":[54],"mask":[55],"reweighting":[56],"downweight":[58],"penumbra":[59],"regions":[60],"during":[61],"training":[62],"apply":[64],"edge":[65],"masks":[66],"at":[67],"final":[69],"decoder":[70],"stage":[71],"for":[72],"better":[73],"supervision.":[74],"For":[75],"temporal":[76,100],"of":[78],"variable":[79],"shapes,":[81],"propose":[83],"Tokenized":[85],"Temporal":[86],"(TTB)":[88],"that":[89],"decouples":[90],"spatiotemporal":[91],"learning.":[92],"TTB":[93],"summarizes":[94],"cross-frame":[95],"semantics":[97],"into":[98],"learnable":[99],"tokens,":[101],"enabling":[102],"efficient":[103],"sequence":[104],"encoding":[105],"with":[106],"minimal":[107],"computation":[108],"overhead.":[109],"Comprehensive":[110],"Experiments":[111],"on":[112],"multiple":[113],"benchmark":[114],"datasets":[115],"demonstrate":[116],"state-of-the-art":[117],"accuracy":[118],"real-time":[120],"inference":[121],"efficiency.":[122]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}
