{"id":"https://openalex.org/W4414079671","doi":"https://doi.org/10.26599/cvm.2025.9450504","title":"ImVoxelENet: Image to Voxels Epipolar Transformer for Multi-View RGB-Based 3D Object Detection","display_name":"ImVoxelENet: Image to Voxels Epipolar Transformer for Multi-View RGB-Based 3D Object Detection","publication_year":2025,"publication_date":"2025-08-01","ids":{"openalex":"https://openalex.org/W4414079671","doi":"https://doi.org/10.26599/cvm.2025.9450504"},"language":"en","primary_location":{"id":"doi:10.26599/cvm.2025.9450504","is_oa":true,"landing_page_url":"https://doi.org/10.26599/cvm.2025.9450504","pdf_url":null,"source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.26599/cvm.2025.9450504","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073840367","display_name":"Gang Xu","orcid":"https://orcid.org/0000-0001-7569-384X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gang Xu","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University,Beijing,China,100191","School of Computer Science and Engineering, Beihang University, Beijing 100191, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444762","display_name":"Haoyu Liu","orcid":"https://orcid.org/0000-0003-3755-5184"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Liu","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University,Beijing,China,100191","School of Computer Science and Engineering, Beihang University, Beijing 100191, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074480499","display_name":"Biao Leng","orcid":"https://orcid.org/0000-0003-3588-5622"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Leng","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University,Beijing,China,100191","School of Computer Science and Engineering, Beihang University, Beijing 100191, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100442122","display_name":"Xiong Zhang","orcid":"https://orcid.org/0000-0002-9214-396X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Xiong","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University,Beijing,China,100191","School of Computer Science and Engineering, Beihang University, Beijing 100191, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073840367"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24787728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"4","first_page":"871","last_page":"888"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.7896000146865845,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.7896000146865845,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.7750999927520752,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.7591000199317932,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/epipolar-geometry","display_name":"Epipolar geometry","score":0.9747999906539917},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.5311999917030334},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.453000009059906},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.41690000891685486},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.41029998660087585},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.3472999930381775},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.33090001344680786},{"id":"https://openalex.org/keywords/fundamental-matrix","display_name":"Fundamental matrix (linear differential equation)","score":0.3199999928474426}],"concepts":[{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.9747999906539917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8174999952316284},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.8069999814033508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6765000224113464},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.5311999917030334},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.453000009059906},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.41029998660087585},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C2780427248","wikidata":"https://www.wikidata.org/wiki/Q17014996","display_name":"Fundamental matrix (linear differential equation)","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.31439998745918274},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2824999988079071},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.28189998865127563},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.28130000829696655},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2809000015258789},{"id":"https://openalex.org/C44185422","wikidata":"https://www.wikidata.org/wiki/Q6002064","display_name":"Image-based modeling and rendering","level":3,"score":0.27799999713897705},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.26599/cvm.2025.9450504","is_oa":true,"landing_page_url":"https://doi.org/10.26599/cvm.2025.9450504","pdf_url":null,"source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c10d666a6aea4cb28b1b6f0bb2336d27","is_oa":true,"landing_page_url":"https://doaj.org/article/c10d666a6aea4cb28b1b6f0bb2336d27","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Visual Media, Vol 11, Iss 4, Pp 871-888 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.26599/cvm.2025.9450504","is_oa":true,"landing_page_url":"https://doi.org/10.26599/cvm.2025.9450504","pdf_url":null,"source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W2194775991","https://openalex.org/W2563100679","https://openalex.org/W2594519801","https://openalex.org/W2598108580","https://openalex.org/W2625169091","https://openalex.org/W2769312834","https://openalex.org/W2897529137","https://openalex.org/W2904332125","https://openalex.org/W2963150697","https://openalex.org/W2963601843","https://openalex.org/W2968296999","https://openalex.org/W2973014570","https://openalex.org/W2988715931","https://openalex.org/W3012271043","https://openalex.org/W3034429258","https://openalex.org/W3034801905","https://openalex.org/W3035424742","https://openalex.org/W3035563424","https://openalex.org/W3096754345","https://openalex.org/W3109428934","https://openalex.org/W3114438877","https://openalex.org/W3133884127","https://openalex.org/W3155772318","https://openalex.org/W3159717817","https://openalex.org/W3167095230","https://openalex.org/W3171032126","https://openalex.org/W3175844808","https://openalex.org/W3176368002","https://openalex.org/W3179877418","https://openalex.org/W3185394819","https://openalex.org/W3187760974","https://openalex.org/W3201719054","https://openalex.org/W3203127407","https://openalex.org/W3204832889","https://openalex.org/W3215207332","https://openalex.org/W4200074884","https://openalex.org/W4284964857","https://openalex.org/W4288391480","https://openalex.org/W4312878643","https://openalex.org/W4313153367","https://openalex.org/W4367182782","https://openalex.org/W4383502754","https://openalex.org/W4384519104","https://openalex.org/W4385552743","https://openalex.org/W4386066615","https://openalex.org/W4386075853","https://openalex.org/W4388052703","https://openalex.org/W4388757371","https://openalex.org/W4390872444","https://openalex.org/W4390872749","https://openalex.org/W4390873153","https://openalex.org/W4390873371","https://openalex.org/W4390874146","https://openalex.org/W4390874598","https://openalex.org/W4393149498","https://openalex.org/W4393156295","https://openalex.org/W4396941548","https://openalex.org/W4402727002","https://openalex.org/W4404002903","https://openalex.org/W4404294186","https://openalex.org/W4410738505"],"related_works":["https://openalex.org/W4251504644","https://openalex.org/W132764016","https://openalex.org/W2148054235","https://openalex.org/W2132043085","https://openalex.org/W2123437433","https://openalex.org/W2369285629","https://openalex.org/W2105565426","https://openalex.org/W2737258383","https://openalex.org/W2101703235","https://openalex.org/W2935803391"],"abstract_inverted_index":{"The":[0,20],"task":[1],"of":[2,17,52,63,91,120],"detecting":[3],"three-dimensional":[4],"objects":[5],"using":[6],"only":[7],"RGB":[8],"images":[9],"presents":[10],"a":[11,76,82,132,145],"considerable":[12],"challenge":[13],"within":[14],"the":[15,60,64,89,101,109,117],"domain":[16],"computer":[18],"vision.":[19],"core":[21],"issue":[22],"lies":[23],"in":[24,46,59,148,153],"accurately":[25],"performing":[26],"epipolar":[27,43,84,127],"geometry":[28],"matching":[29],"between":[30,103,126],"multiple":[31,112],"views":[32],"to":[33],"obtain":[34],"latent":[35],"geometric":[36,83,121],"priors.":[37],"Existing":[38],"methods":[39],"establish":[40],"correspondences":[41,122],"along":[42,108],"line":[44],"features":[45,93,107],"voxel":[47],"space":[48],"through":[49],"various":[50],"layers":[51],"convolution.":[53],"However,":[54],"this":[55,72],"step":[56],"often":[57],"occurs":[58],"later":[61],"stages":[62],"network,":[65],"which":[66],"limits":[67],"overall":[68],"performance.":[69,158],"To":[70],"address":[71],"challenge,":[73],"we":[74],"introduce":[75],"novel":[77],"framework,":[78],"ImVoxelENet,":[79],"that":[80,99,140],"integrates":[81],"constraint.":[85],"We":[86],"start":[87],"from":[88],"back-projection":[90],"pixel-wise":[92],"and":[94,105,123,136],"design":[95],"an":[96],"attention":[97],"mechanism":[98],"captures":[100],"relationship":[102],"forward":[104],"backward":[106],"ray":[110],"for":[111],"views.":[113],"This":[114],"approach":[115],"enables":[116],"early":[118],"establishment":[119],"structural":[124],"connections":[125],"lines.":[128],"Using":[129],"ScanNetV2":[130],"as":[131],"benchmark,":[133],"extensive":[134],"comparative":[135],"ablation":[137],"experiments":[138],"demonstrate":[139],"our":[141],"proposed":[142],"network":[143],"achieves":[144],"1.1%":[146],"improvement":[147],"mAP,":[149],"highlighting":[150],"its":[151],"effectiveness":[152],"enhancing":[154],"3D":[155],"object":[156],"detection":[157],"Our":[159],"code":[160],"is":[161],"available":[162],"at":[163],"https://github.com/xug-coder/ImVoxelENet.":[164]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
