{"id":"https://openalex.org/W4308161846","doi":"https://doi.org/10.48550/arxiv.2211.01142","title":"OPA-3D: Occlusion-Aware Pixel-Wise Aggregation for Monocular 3D Object Detection","display_name":"OPA-3D: Occlusion-Aware Pixel-Wise Aggregation for Monocular 3D Object Detection","publication_year":2022,"publication_date":"2022-11-02","ids":{"openalex":"https://openalex.org/W4308161846","doi":"https://doi.org/10.48550/arxiv.2211.01142"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2211.01142","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.01142","pdf_url":"https://arxiv.org/pdf/2211.01142","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2211.01142","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047143300","display_name":"Yongzhi Su","orcid":"https://orcid.org/0000-0003-0843-5917"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Su, Yongzhi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101895081","display_name":"Di Yan","orcid":"https://orcid.org/0000-0003-1977-8448"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di, Yan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006401089","display_name":"Fabian Manhardt","orcid":"https://orcid.org/0000-0002-4577-4590"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manhardt, Fabian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055662103","display_name":"Guangyao Zhai","orcid":"https://orcid.org/0000-0002-1527-5387"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhai, Guangyao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000984202","display_name":"Jason Rambach","orcid":"https://orcid.org/0000-0001-8122-6789"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rambach, Jason","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067135033","display_name":"Benjamin Busam","orcid":"https://orcid.org/0000-0002-0620-5774"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Busam, Benjamin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051650277","display_name":"Didier Stricker","orcid":"https://orcid.org/0009-0004-8794-6858"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stricker, Didier","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5041092666","display_name":"Federico Tombari","orcid":"https://orcid.org/0000-0001-5598-5212"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tombari, Federico","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5047143300"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9950000047683716,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.8539983034133911},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6850563287734985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.618439793586731},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.603652834892273},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5213778614997864},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5141541957855225},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5082694888114929},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4930536448955536},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.49041080474853516},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.473977267742157},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4564899802207947},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4356403052806854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2907601594924927},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11688148975372314}],"concepts":[{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.8539983034133911},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6850563287734985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.618439793586731},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.603652834892273},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5213778614997864},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5141541957855225},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5082694888114929},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4930536448955536},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.49041080474853516},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.473977267742157},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4564899802207947},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4356403052806854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2907601594924927},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11688148975372314},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2211.01142","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.01142","pdf_url":"https://arxiv.org/pdf/2211.01142","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2211.01142","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2211.01142","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2211.01142","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.01142","pdf_url":"https://arxiv.org/pdf/2211.01142","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Despite":[0],"monocular":[1],"3D":[2,80,142],"object":[3,42,72,107,143],"detection":[4,78],"having":[5],"recently":[6],"made":[7],"a":[8,53,76,116,189],"significant":[9],"leap":[10],"forward":[11],"thanks":[12],"to":[13,61,83,104,128,154,195],"the":[14,36,89,94,106,137,161,167,173,183],"use":[15],"of":[16,33,79,163],"pre-trained":[17],"depth":[18,40,66,99],"estimators":[19],"for":[20],"pseudo-LiDAR":[21],"recovery,":[22],"such":[23],"two-stage":[24],"methods":[25,181],"typically":[26],"suffer":[27],"from":[28],"overfitting":[29],"and":[30,41,71,100,145,199],"are":[31],"incapable":[32],"explicitly":[34],"encapsulating":[35],"geometric":[37],"relation":[38],"between":[39],"bounding":[43,73,108,117],"box.":[44],"To":[45],"overcome":[46],"this":[47],"limitation,":[48],"we":[49],"instead":[50],"propose":[51],"OPA-3D,":[52],"single-stage,":[54],"end-to-end,":[55],"Occlusion-Aware":[56],"Pixel-Wise":[57],"Aggregation":[58],"network":[59],"that":[60,177],"jointly":[62],"estimate":[63],"dense":[64],"scene":[65],"with":[67],"depth-bounding":[68,101],"box":[69,102,109,118],"residuals":[70,103],"boxes,":[74],"allowing":[75],"two-stream":[77,149],"objects,":[81],"leading":[82],"significantly":[84],"more":[85],"robust":[86],"detections.":[87],"Thereby,":[88],"geometry":[90,120],"stream":[91],"denoted":[92],"as":[93,136],"Geometry":[95],"Stream,":[96,139],"combines":[97],"visible":[98],"recover":[105],"via":[110],"explicit":[111],"occlusion-aware":[112],"optimization.":[113],"In":[114],"addition,":[115],"based":[119],"projection":[121],"scheme":[122],"is":[123],"employed":[124],"in":[125],"an":[126],"effort":[127],"enhance":[129],"distance":[130],"perception.":[131],"The":[132],"second":[133],"stream,":[134],"named":[135],"Context":[138],"directly":[140],"regresses":[141],"location":[144],"size.":[146],"This":[147],"novel":[148],"representation":[150],"further":[151],"enables":[152],"us":[153],"enforce":[155],"cross-stream":[156],"consistency":[157],"terms":[158],"which":[159],"aligns":[160],"outputs":[162],"both":[164],"streams,":[165],"improving":[166],"overall":[168],"performance.":[169],"Extensive":[170],"experiments":[171],"on":[172,182],"public":[174],"benchmark":[175],"demonstrate":[176],"OPA-3D":[178],"outperforms":[179],"state-of-the-art":[180],"main":[184],"Car":[185],"category,":[186],"whilst":[187],"keeping":[188],"real-time":[190],"inference":[191],"speed.":[192],"We":[193],"plan":[194],"release":[196],"all":[197],"codes":[198],"trained":[200],"models":[201],"soon.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2022-11-08T00:00:00"}
