{"id":"https://openalex.org/W4388206429","doi":"https://doi.org/10.1145/3604078.3604119","title":"Generic Skeleton Object Detection Framework with Gradient Maps","display_name":"Generic Skeleton Object Detection Framework with Gradient Maps","publication_year":2023,"publication_date":"2023-05-19","ids":{"openalex":"https://openalex.org/W4388206429","doi":"https://doi.org/10.1145/3604078.3604119"},"language":"en","primary_location":{"id":"doi:10.1145/3604078.3604119","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604078.3604119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th International Conference on Digital Image Processing","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/A5073752594","display_name":"Futian Wang","orcid":"https://orcid.org/0000-0003-4181-8485"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Futian Wang","raw_affiliation_strings":["Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University, China and \rHefei Comprehensive National Science Center and Suzhou Glink IoT Technology Co. Ltd, China"],"raw_orcid":"https://orcid.org/0000-0003-4181-8485","affiliations":[{"raw_affiliation_string":"Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University, China and \rHefei Comprehensive National Science Center and Suzhou Glink IoT Technology Co. Ltd, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101459217","display_name":"Feier Chen","orcid":"https://orcid.org/0009-0008-2366-6338"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feier Chen","raw_affiliation_strings":["Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University, China"],"raw_orcid":"https://orcid.org/0009-0008-2366-6338","affiliations":[{"raw_affiliation_string":"Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jin Tang","orcid":"https://orcid.org/0000-0002-2194-0179"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Tang","raw_affiliation_strings":["Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University, China"],"raw_orcid":"https://orcid.org/0000-0002-2194-0179","affiliations":[{"raw_affiliation_string":"Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023147010","display_name":"Mengyu Huang","orcid":"https://orcid.org/0009-0001-8412-7433"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengyu Huang","raw_affiliation_strings":["Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University, China"],"raw_orcid":"https://orcid.org/0009-0001-8412-7433","affiliations":[{"raw_affiliation_string":"Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13402196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9987000226974487,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958999752998352,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7037091255187988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.697728157043457},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6738249659538269},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6029267907142639},{"id":"https://openalex.org/keywords/skeleton","display_name":"Skeleton (computer programming)","score":0.5989116430282593},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5605801343917847},{"id":"https://openalex.org/keywords/sharpening","display_name":"Sharpening","score":0.514241635799408},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.48037630319595337},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.47755154967308044},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4583510756492615},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4567680358886719},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.44696590304374695},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4100586771965027},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3839500844478607}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7037091255187988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.697728157043457},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6738249659538269},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6029267907142639},{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.5989116430282593},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5605801343917847},{"id":"https://openalex.org/C2781137444","wikidata":"https://www.wikidata.org/wiki/Q237105","display_name":"Sharpening","level":2,"score":0.514241635799408},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.48037630319595337},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.47755154967308044},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4583510756492615},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4567680358886719},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44696590304374695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4100586771965027},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3839500844478607},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3604078.3604119","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604078.3604119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th International Conference on Digital Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2120419212","https://openalex.org/W2141357020","https://openalex.org/W2161969291","https://openalex.org/W2164598857","https://openalex.org/W2166706236","https://openalex.org/W2168356304","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2884561390","https://openalex.org/W2909888383","https://openalex.org/W2911495555","https://openalex.org/W2963037989","https://openalex.org/W2963857746","https://openalex.org/W2964241181","https://openalex.org/W2982770724","https://openalex.org/W2988452521","https://openalex.org/W3157042932","https://openalex.org/W6684249991"],"related_works":["https://openalex.org/W4327500857","https://openalex.org/W2965994363","https://openalex.org/W4311223090","https://openalex.org/W1689909837","https://openalex.org/W4205729548","https://openalex.org/W4298525700","https://openalex.org/W1895541646","https://openalex.org/W2953362004","https://openalex.org/W2952251705","https://openalex.org/W2889698616"],"abstract_inverted_index":{"In":[0],"real-world":[1],"applications,":[2],"we":[3,15,52,92,165],"find":[4],"a":[5,21,39,120],"special":[6],"type":[7],"of":[8,25,35,41,63,107,110],"object":[9,124,138],"with":[10,77,85,129],"poor":[11],"detection":[12,61,139,173],"results,":[13],"which":[14,87],"call":[16],"skeleton":[17,36,64,123],"objects.":[18,65],"They":[19],"have":[20],"relatively":[22],"small":[23],"percentage":[24],"truly":[26],"meaningful":[27],"pixels":[28],"in":[29,135,158],"the":[30,60,67,74,82,94,101,105,111,115,155,163],"bounding":[31],"box.":[32],"The":[33],"hollows":[34],"objects":[37],"contain":[38],"lot":[40],"cluttered":[42],"background":[43,83],"information.":[44],"Through":[45],"observation":[46],"and":[47,80,146,148],"experience":[48],"from":[49],"previous":[50],"practice,":[51],"try":[53],"to":[54,58,72,99,154,171],"use":[55],"gradient":[56,68,102],"map":[57,69,103],"improve":[59],"results":[62],"Because":[66],"is":[70,151],"equivalent":[71],"sharpening":[73],"foreground":[75],"information":[76,84,109],"regular":[78],"texture":[79],"smoothing":[81],"clutter,":[86],"meets":[88],"our":[89,149],"requirements.":[90],"So":[91],"propose":[93],"GAM":[95],"(gradient":[96],"attention":[97],"module)":[98],"let":[100],"guide":[104],"learning":[106],"semantic":[108],"original":[112],"image":[113],"by":[114],"network.":[116],"We":[117,132],"also":[118],"construct":[119],"dataset":[121],"for":[122],"detection,":[125],"containing":[126],"3131":[127],"images":[128],"7":[130],"categories.":[131,161],"conduct":[133],"experiments":[134],"several":[136],"state-of-the-art":[137],"frameworks":[140],"such":[141],"as":[142],"Faster":[143],"R-CNN,":[144],"RetinaNet,":[145],"YOLOv5,":[147],"method":[150,164],"obviously":[152],"superior":[153],"corresponding":[156],"baseline":[157],"almost":[159],"all":[160],"Meanwhile":[162],"proposed":[166],"can":[167],"be":[168],"easily":[169],"generalized":[170],"various":[172],"frameworks.":[174],"`1`":[175]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
