{"id":"https://openalex.org/W4415743494","doi":"https://doi.org/10.1109/tpami.2025.3627192","title":"Joint Sparse Optical Flow Estimation and Keypoint Detection via Dual-task Imperative Learning","display_name":"Joint Sparse Optical Flow Estimation and Keypoint Detection via Dual-task Imperative Learning","publication_year":2025,"publication_date":"2025-10-31","ids":{"openalex":"https://openalex.org/W4415743494","doi":"https://doi.org/10.1109/tpami.2025.3627192","pmid":"https://pubmed.ncbi.nlm.nih.gov/41171660"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3627192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3627192","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5009973955","display_name":"Qiang Liu","orcid":"https://orcid.org/0000-0001-7017-2367"},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiang Liu","raw_affiliation_strings":["College of Machinery and Power Engineering, Three Gorges University, Yichang, China","College of Machinery and Power Engineering, Three Gorges University, Yichang, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0001-7017-2367","affiliations":[{"raw_affiliation_string":"College of Machinery and Power Engineering, Three Gorges University, Yichang, China","institution_ids":["https://openalex.org/I161350542"]},{"raw_affiliation_string":"College of Machinery and Power Engineering, Three Gorges University, Yichang, Hubei, China","institution_ids":["https://openalex.org/I161350542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036240731","display_name":"Baojia Chen","orcid":"https://orcid.org/0000-0003-4305-0051"},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baojia Chen","raw_affiliation_strings":["College of Machinery and Power Engineering, Three Gorges University, Yichang, China","College of Machinery and Power Engineering, Three Gorges University, Yichang, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0003-4305-0051","affiliations":[{"raw_affiliation_string":"College of Machinery and Power Engineering, Three Gorges University, Yichang, China","institution_ids":["https://openalex.org/I161350542"]},{"raw_affiliation_string":"College of Machinery and Power Engineering, Three Gorges University, Yichang, Hubei, China","institution_ids":["https://openalex.org/I161350542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055545502","display_name":"Zhiqiang Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Hao","raw_affiliation_strings":["School of Metallurgical and Ecological Engineering, Wuhan University of Science and Technology, Wuhan, China","School of Metallurgical and Ecological Engineering, Wuhan University of Science and Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Metallurgical and Ecological Engineering, Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]},{"raw_affiliation_string":"School of Metallurgical and Ecological Engineering, Wuhan University of Science and Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xinlong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinlong Li","raw_affiliation_strings":["College of Machinery and Power Engineering, Three Gorges University, Yichang, China","College of Machinery and Power Engineering, Three Gorges University, Yichang, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Machinery and Power Engineering, Three Gorges University, Yichang, China","institution_ids":["https://openalex.org/I161350542"]},{"raw_affiliation_string":"College of Machinery and Power Engineering, Three Gorges University, Yichang, Hubei, China","institution_ids":["https://openalex.org/I161350542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110272125","display_name":"Leilei Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094336","display_name":"Hubei Water Resources Research Institute","ror":"https://ror.org/007amws38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leilei Xiang","raw_affiliation_strings":["National Engineering Research Center of Water Resources Efficient Utilization and Engineering, Wuhan, China","National Engineering Research Center of Water Resources Efficient Utilization and Engineering, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Research Center of Water Resources Efficient Utilization and Engineering, Wuhan, China","institution_ids":["https://openalex.org/I4210094336"]},{"raw_affiliation_string":"National Engineering Research Center of Water Resources Efficient Utilization and Engineering, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4210094336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111545991","display_name":"Juan Liu","orcid":"https://orcid.org/0000-0002-5515-5611"},"institutions":[{"id":"https://openalex.org/I4210094336","display_name":"Hubei Water Resources Research Institute","ror":"https://ror.org/007amws38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Liu","raw_affiliation_strings":["National Engineering Research Center of Water Resources Efficient Utilization and Engineering, Wuhan, China","National Engineering Research Center of Water Resources Efficient Utilization and Engineering, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Research Center of Water Resources Efficient Utilization and Engineering, Wuhan, China","institution_ids":["https://openalex.org/I4210094336"]},{"raw_affiliation_string":"National Engineering Research Center of Water Resources Efficient Utilization and Engineering, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4210094336"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5009973955"],"corresponding_institution_ids":["https://openalex.org/I161350542"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30389886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":"3","first_page":"2659","last_page":"2675"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9128999710083008,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9128999710083008,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.046799998730421066,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.006099999882280827,"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/optical-flow","display_name":"Optical flow","score":0.8295999765396118},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.781499981880188},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5543000102043152},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.46389999985694885},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.4284999966621399},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4284000098705292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41200000047683716},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.390500009059906},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.3896999955177307},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"Visual odometry","score":0.38909998536109924}],"concepts":[{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.8295999765396118},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.781499981880188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7166000008583069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7160000205039978},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5543000102043152},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5005000233650208},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.46389999985694885},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.4284999966621399},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4284000098705292},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42160001397132874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.390500009059906},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.38909998536109924},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.29829999804496765},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.28040000796318054},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2678999900817871},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C132771110","wikidata":"https://www.wikidata.org/wiki/Q506922","display_name":"Adaptive optics","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3627192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3627192","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:41171660","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41171660","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8078027619","display_name":null,"funder_award_id":"MECOF2022B02","funder_id":"https://openalex.org/F4320325431","funder_display_name":"Wuhan University of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320312071","display_name":"Ministry of Education, Libya","ror":"https://ror.org/02w030k33"},{"id":"https://openalex.org/F4320325431","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W764651262","https://openalex.org/W1513100184","https://openalex.org/W1578285471","https://openalex.org/W1590329763","https://openalex.org/W1904063580","https://openalex.org/W2035379092","https://openalex.org/W2040378863","https://openalex.org/W2117228865","https://openalex.org/W2124274017","https://openalex.org/W2130103520","https://openalex.org/W2150066425","https://openalex.org/W2168874984","https://openalex.org/W2259424905","https://openalex.org/W2396274919","https://openalex.org/W2492517581","https://openalex.org/W2560474170","https://openalex.org/W2737590896","https://openalex.org/W2793585103","https://openalex.org/W2904340070","https://openalex.org/W2962864875","https://openalex.org/W2963685263","https://openalex.org/W2963782415","https://openalex.org/W2963891416","https://openalex.org/W3007471652","https://openalex.org/W3009931536","https://openalex.org/W3043075211","https://openalex.org/W3091667825","https://openalex.org/W3109379931","https://openalex.org/W3109908659","https://openalex.org/W3126851256","https://openalex.org/W3132270109","https://openalex.org/W3166285241","https://openalex.org/W3174911623","https://openalex.org/W4249022109","https://openalex.org/W4304140361","https://openalex.org/W4312563719","https://openalex.org/W4312790276","https://openalex.org/W4386075620","https://openalex.org/W4400023330","https://openalex.org/W4402716219","https://openalex.org/W4403068931"],"related_works":[],"abstract_inverted_index":{"Contemporary":[0],"deep":[1],"learning":[2,82,132],"approaches":[3],"for":[4,160,163],"optical":[5,49,63,68,88],"flow":[6,50,64,69,89],"estimation":[7,65,90],"continue":[8],"to":[9],"face":[10],"persistent":[11],"challenges":[12],"in":[13,31],"model":[14],"interpretability,":[15],"generalization":[16],"capacity,":[17],"and":[18,62,106,140,152],"deployment":[19],"efficiency,":[20],"significantly":[21],"constraining":[22],"their":[23],"practical":[24],"implementation.":[25],"This":[26,116],"limitation":[27],"becomes":[28],"particularly":[29],"critical":[30],"applications":[32],"such":[33],"as":[34],"visual":[35],"odometry":[36],"(VO),":[37],"where":[38,104],"precise":[39],"sparse":[40,67,87],"point":[41],"tracking":[42],"supersedes":[43],"the":[44,53,124],"conventional":[45],"emphasis":[46],"on":[47],"dense":[48],"accuracy.":[51],"Moreover,":[52],"lack":[54],"of":[55],"a":[56,78,112],"joint":[57],"framework":[58,83,136],"combining":[59],"keypoint":[60,94],"detection":[61,95],"limits":[66],"performance.":[70],"To":[71],"address":[72],"these":[73],"fundamental":[74],"issues,":[75],"we":[76],"propose":[77],"novel":[79],"dual-task":[80],"imperative":[81,131],"that":[84],"synergistically":[85],"optimizes":[86],"(iFLOW)":[91],"with":[92,137],"adaptive":[93],"(iPOINT).":[96],"Our":[97],"methodology":[98],"implements":[99],"an":[100],"Expectation-Maximization":[101],"(EM)":[102],"paradigm":[103],"iFLOW":[105],"iPOINT":[107],"undergo":[108],"alternating":[109],"optimization":[110],"through":[111],"Gauss-Newton":[113],"reasoning":[114],"engine.":[115],"innovative":[117],"architecture":[118],"leverages":[119],"convolutional":[120],"feature":[121,126],"advantages":[122],"under":[123],"generalized":[125],"invariance":[127],"principle.":[128],"The":[129],"resulting":[130],"mechanism":[133],"imbues":[134],"our":[135,155],"enchanced":[138],"interpretability":[139],"cross-domain":[141],"adaptability":[142],"while":[143],"maintaining":[144],"computational":[145],"efficiency.":[146],"Through":[147],"comparative":[148],"evaluations":[149],"against":[150],"classical":[151],"learning-based":[153],"baselines,":[154],"ultra-compact":[156],"models":[157],"(0.05M":[158],"parameters":[159],"iFLOW,":[161],"0.09M":[162],"iPOINT)":[164],"demonstrate":[165],"remarkable":[166],"performance":[167],"across":[168],"multiple":[169],"metrics":[170],"(End-point":[171],"Error,":[172],"F1-all,":[173],"VO":[174],"trajectory":[175],"accuracy)":[176],"despite":[177],"requiring":[178],"only":[179],"200":[180],"training":[181],"image":[182],"pairs.":[183]},"counts_by_year":[],"updated_date":"2026-02-07T06:11:34.122080","created_date":"2025-10-31T00:00:00"}
