{"id":"https://openalex.org/W7127443195","doi":"https://doi.org/10.1109/ccece64018.2025.11364393","title":"DetTrack: Detect Target from Local Region for 3D Single Object Tracking in Point Clouds","display_name":"DetTrack: Detect Target from Local Region for 3D Single Object Tracking in Point Clouds","publication_year":2025,"publication_date":"2025-05-26","ids":{"openalex":"https://openalex.org/W7127443195","doi":"https://doi.org/10.1109/ccece64018.2025.11364393"},"language":null,"primary_location":{"id":"doi:10.1109/ccece64018.2025.11364393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccece64018.2025.11364393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5124892194","display_name":"Hande Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hande Yin","raw_affiliation_strings":["Dalhousie University,Electrical and Computer Engineering,Halifax,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalhousie University,Electrical and Computer Engineering,Halifax,Canada","institution_ids":["https://openalex.org/I129902397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124921431","display_name":"Wei Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Southern University of Science and Technology,Mechanical and Energy Engineering,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology,Mechanical and Energy Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035085286","display_name":"Jason GU","orcid":null},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jason Gu","raw_affiliation_strings":["Dalhousie University,Electrical and Computer Engineering,Halifax,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalhousie University,Electrical and Computer Engineering,Halifax,Canada","institution_ids":["https://openalex.org/I129902397"]}]}],"institutions":[],"countries_distinct_count":2,"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":null,"issue":null,"first_page":"298","last_page":"304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.7559000253677368,"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":0.7559000253677368,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.10019999742507935,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.020400000736117363,"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/detector","display_name":"Detector","score":0.6090999841690063},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5616000294685364},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5595999956130981},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5382000207901001},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5289999842643738},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.5281000137329102},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4507000148296356},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4361000061035156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7748000025749207},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6984000205993652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6707000136375427},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6090999841690063},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5616000294685364},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5595999956130981},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5382000207901001},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5289999842643738},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.5281000137329102},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4507000148296356},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.3939000070095062},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.3375999927520752},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccece64018.2025.11364393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccece64018.2025.11364393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2158827467","https://openalex.org/W2949708697","https://openalex.org/W2962922818","https://openalex.org/W2968296999","https://openalex.org/W2988715931","https://openalex.org/W2997941866","https://openalex.org/W3034314779","https://openalex.org/W3035574168","https://openalex.org/W3035641096","https://openalex.org/W3093537218","https://openalex.org/W3118341329","https://openalex.org/W3167095230","https://openalex.org/W3194700450","https://openalex.org/W3208501016","https://openalex.org/W4210786150","https://openalex.org/W4312571097","https://openalex.org/W4312950653","https://openalex.org/W4313057812","https://openalex.org/W4321482282","https://openalex.org/W4367359633","https://openalex.org/W4382203498","https://openalex.org/W4382464387","https://openalex.org/W4382568075","https://openalex.org/W4385767918","https://openalex.org/W4411244793","https://openalex.org/W4413925437","https://openalex.org/W7105833406"],"related_works":[],"abstract_inverted_index":{"D":[0],"single":[1],"object":[2,45,114],"tracking":[3,100,120],"(3D":[4],"SOT)":[5],"is":[6,57],"an":[7],"essential":[8],"task":[9],"in":[10,15,33,43],"computer":[11],"vision,":[12],"widely":[13],"applied":[14],"autonomous":[16],"driving":[17],"and":[18,22,29,37,102,130,154],"robotics.":[19],"Existing":[20],"Siamese-based":[21],"motion-centric":[23],"methods":[24,169],"often":[25],"require":[26],"additional":[27],"parameters":[28],"specialized":[30,126],"architectures,":[31],"resulting":[32],"high":[34],"computational":[35,133],"demands":[36],"failing":[38],"to":[39,94,108,142,165],"fully":[40],"utilize":[41],"advancements":[42],"3D":[44,60,81,105,111,127,137,147,167],"detection.":[46],"In":[47],"this":[48,75],"paper,":[49],"we":[50,77],"believe":[51],"that":[52,159],"if":[53],"the":[54,96,119,123,136,150],"search":[55,91],"region":[56,92,98],"sufficiently":[58],"localized,":[59],"SOT":[61,82,128,168],"can":[62],"be":[63],"reformulated":[64],"as":[65],"a":[66,79,90,103],"sequential":[67],"detection":[68],"problem":[69],"within":[70],"these":[71],"regions.":[72],"Based":[73],"on":[74,170],"insight,":[76],"propose":[78],"novel":[80],"framework,":[83],"DetTrack,":[84],"which":[85],"comprises":[86],"two":[87],"core":[88],"components:":[89],"estimator":[93],"predict":[95],"potential":[97],"including":[99],"target,":[101],"modular":[104],"detector":[106,138],"switcher":[107,139],"integrate":[109,144],"pretrained":[110],"detectors":[112],"for":[113,125],"localization.":[115],"Our":[116],"framework":[117,151],"simplifies":[118],"pipeline,":[121],"eliminates":[122],"need":[124],"models,":[129],"significantly":[131],"reduces":[132],"costs.":[134],"Furthermore,":[135],"enables":[140],"DetTrack":[141],"seamlessly":[143],"various":[145],"state-of-the-art":[146,166],"detectors,":[148],"making":[149],"highly":[152],"adaptable":[153],"future-proof.":[155],"Experimental":[156],"results":[157],"demonstrate":[158],"our":[160],"method":[161],"achieves":[162],"performance":[163],"comparable":[164],"multiple":[171],"datasets":[172],"while":[173],"enabling":[174],"real-time":[175],"inference":[176],"speed.":[177]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-04T00:00:00"}
