{"id":"https://openalex.org/W4415536216","doi":"https://doi.org/10.1145/3746027.3755007","title":"Video Instance Segmentation by Weighted Structure Inference","display_name":"Video Instance Segmentation by Weighted Structure Inference","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415536216","doi":"https://doi.org/10.1145/3746027.3755007"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755007","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062453382","display_name":"Zheyun Qin","orcid":"https://orcid.org/0000-0003-2564-071X"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zheyun Qin","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101921698","display_name":"Yu Deng","orcid":"https://orcid.org/0000-0003-2343-3688"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I4210134002","display_name":"Shandong University of Art and Design","ror":"https://ror.org/034p36h22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210134002"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deng Yu","raw_affiliation_strings":["School of Artificial Intelligence, Shandong University, Jinan, Shandong, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shandong University, Jinan, Shandong, China","institution_ids":["https://openalex.org/I4210134002","https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101935426","display_name":"Yang Shi","orcid":"https://orcid.org/0000-0003-2515-1588"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I4210134002","display_name":"Shandong University of Art and Design","ror":"https://ror.org/034p36h22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210134002"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Shi","raw_affiliation_strings":["School of Artificial Intelligence, Shandong University, Jinan, Shandong, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shandong University, Jinan, Shandong, China","institution_ids":["https://openalex.org/I4210134002","https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080221133","display_name":"Qiangchang Wang","orcid":"https://orcid.org/0000-0003-3707-1761"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiangchang Wang","raw_affiliation_strings":["School of Software, Shandong University, Jinan, Shandong, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, Shandong, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050947285","display_name":"Zhumin Chen","orcid":"https://orcid.org/0000-0003-4592-4074"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I4210134002","display_name":"Shandong University of Art and Design","ror":"https://ror.org/034p36h22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210134002"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhumin Chen","raw_affiliation_strings":["School of Artificial Intelligence, Shandong University, Jinan, Shandong, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shandong University, Jinan, Shandong, China","institution_ids":["https://openalex.org/I4210134002","https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5062453382"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30312277,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7616","last_page":"7624"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9997000098228455,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9997000098228455,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9993000030517578,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9988999962806702,"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/segmentation","display_name":"Segmentation","score":0.6897000074386597},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6599000096321106},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5134999752044678},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43070000410079956},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4156000018119812},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.4043999910354614},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.39890000224113464},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3894999921321869},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.3594000041484833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7384999990463257},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6897000074386597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6682999730110168},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6599000096321106},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5134999752044678},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43070000410079956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.423799991607666},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4156000018119812},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.4043999910354614},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3894999921321869},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.3594000041484833},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.34389999508857727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2978000044822693},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.28200000524520874},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27410000562667847},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.251800000667572},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755007","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2019106840","https://openalex.org/W2892880750","https://openalex.org/W2966720510","https://openalex.org/W2982723417","https://openalex.org/W3035549667","https://openalex.org/W3171516518","https://openalex.org/W3202509201","https://openalex.org/W3212555189","https://openalex.org/W4285236514","https://openalex.org/W4312815172","https://openalex.org/W4312868348","https://openalex.org/W4367595576","https://openalex.org/W4388286369","https://openalex.org/W4390873987","https://openalex.org/W4403780519","https://openalex.org/W4403944003","https://openalex.org/W4404123597","https://openalex.org/W4405227245","https://openalex.org/W4406091913"],"related_works":[],"abstract_inverted_index":{"Video":[0,81,186],"instance":[1,168,181],"segmentation":[2,182],"presents":[3],"significant":[4],"challenges":[5],"in":[6,26,127,184],"complex":[7,60,101],"and":[8,52,62,123,163,188],"dynamic":[9,68,138],"environments,":[10],"where":[11],"instances":[12,162],"experience":[13],"progressive":[14],"occlusion,":[15],"either":[16],"from":[17],"objects":[18],"obstructing":[19],"each":[20,94],"other":[21],"or":[22],"due":[23],"to":[24,43,50,58,65,67,147],"changes":[25],"the":[27,48,56,63,75,98,121,128,157,165],"camera's":[28],"viewpoint.":[29],"Current":[30],"state-of-the-art":[31],"methods":[32],"rely":[33],"on":[34,86,142],"memory":[35],"bank":[36],"mechanisms,":[37],"but":[38],"we":[39,73,113,131],"still":[40],"look":[41],"forward":[42],"new":[44],"paradigms":[45],"that":[46,103,175],"have":[47],"ability":[49,57],"capture":[51,99],"utilize":[53],"structural":[54,88,124,149],"information,":[55],"model":[59,110],"relationships,":[61],"flexibility":[64],"adapt":[66],"scenarios.":[69],"To":[70,109],"this":[71],"end,":[72],"propose":[74],"Weighted":[76,115,143],"Structure":[77],"Inference":[78],"method":[79,155,177],"for":[80,93],"Instance":[82,187],"Segmentation.":[83],"We":[84],"build":[85],"high-order":[87],"relationships":[89],"by":[90,135],"constructing":[91],"hypergraphs":[92],"video":[95,180],"frame,":[96],"enabling":[97],"of":[100,160,167],"interactions":[102],"go":[104],"beyond":[105],"traditional":[106],"pairwise":[107],"methods.":[108],"intricate":[111],"dynamics,":[112],"introduce":[114],"Sheaf":[116],"Hypergraph":[117],"Convolution,":[118],"which":[119],"enhances":[120],"hierarchical":[122],"information":[125],"embedded":[126],"hypergraph.":[129],"Furthermore,":[130],"ensure":[132],"spatio-temporal":[133],"consistency":[134],"employing":[136],"a":[137],"inference":[139],"mechanism":[140],"based":[141],"Sliced":[144],"Wasserstein":[145],"distance":[146],"compare":[148],"features":[150],"across":[151,170],"adjacent":[152],"frames.":[153,171],"Our":[154],"preserves":[156],"topological":[158],"characteristics":[159],"occlusion":[161],"improves":[164],"reliability":[166],"tracking":[169],"Experimental":[172],"results":[173],"demonstrate":[174],"our":[176],"outperforms":[178],"existing":[179],"frameworks":[183],"both":[185],"Panoptic":[189],"Segmentation":[190],"tasks.":[191]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-25T00:00:00"}