{"id":"https://openalex.org/W4399419060","doi":"https://doi.org/10.1145/3652583.3658050","title":"ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation","display_name":"ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation","publication_year":2024,"publication_date":"2024-05-30","ids":{"openalex":"https://openalex.org/W4399419060","doi":"https://doi.org/10.1145/3652583.3658050"},"language":"en","primary_location":{"id":"doi:10.1145/3652583.3658050","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658050","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658050","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658050","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021141988","display_name":"Zhaoxin Fan","orcid":"https://orcid.org/0000-0002-6324-1712"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhaoxin Fan","raw_affiliation_strings":["Renmin University of China & Psyche AI Inc, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6324-1712","affiliations":[{"raw_affiliation_string":"Renmin University of China & Psyche AI Inc, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090587210","display_name":"Zhenbo Song","orcid":"https://orcid.org/0000-0002-5020-4277"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenbo Song","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5020-4277","affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012553687","display_name":"Zhicheng Wang","orcid":"https://orcid.org/0009-0001-4334-3084"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhicheng Wang","raw_affiliation_strings":["Xreal, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-4334-3084","affiliations":[{"raw_affiliation_string":"Xreal, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030023838","display_name":"Jian Hui Xu","orcid":"https://orcid.org/0009-0001-1090-6207"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Xu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-1090-6207","affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020455374","display_name":"Kejian Wu","orcid":"https://orcid.org/0000-0002-2679-2320"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kejian Wu","raw_affiliation_strings":["Xreal, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2679-2320","affiliations":[{"raw_affiliation_string":"Xreal, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100332465","display_name":"Hongyan Liu","orcid":"https://orcid.org/0000-0002-4902-1078"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4902-1078","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100766741","display_name":"Jun He","orcid":"https://orcid.org/0000-0003-1511-7554"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun He","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1511-7554","affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5021141988"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":4.7328,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.95434755,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"55","last_page":"63"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10653","display_name":"Robot Manipulation and Learning","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9829000234603882,"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/pose","display_name":"Pose","score":0.816882848739624},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7550735473632812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6476091146469116},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6416969299316406},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.632634162902832},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6314003467559814},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5460678339004517},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.5296117067337036},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.4903126060962677},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3782500624656677}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.816882848739624},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7550735473632812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6476091146469116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6416969299316406},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.632634162902832},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6314003467559814},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5460678339004517},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.5296117067337036},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.4903126060962677},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3782500624656677},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3652583.3658050","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658050","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658050","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3652583.3658050","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658050","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658050","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399419060.pdf","grobid_xml":"https://content.openalex.org/works/W4399419060.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1820657498","https://openalex.org/W2041376653","https://openalex.org/W2128019145","https://openalex.org/W2194775991","https://openalex.org/W2560023338","https://openalex.org/W2748217987","https://openalex.org/W2752782242","https://openalex.org/W2768879211","https://openalex.org/W2780046032","https://openalex.org/W2956121407","https://openalex.org/W2962770929","https://openalex.org/W2962783853","https://openalex.org/W2962793481","https://openalex.org/W2963150697","https://openalex.org/W2963756608","https://openalex.org/W2963892972","https://openalex.org/W2981378444","https://openalex.org/W2997337685","https://openalex.org/W3009516594","https://openalex.org/W3034597466","https://openalex.org/W3034986117","https://openalex.org/W3035172746","https://openalex.org/W3035355652","https://openalex.org/W3035551320","https://openalex.org/W3107992529","https://openalex.org/W3108671865","https://openalex.org/W3139887931","https://openalex.org/W3163945288","https://openalex.org/W3173744995","https://openalex.org/W3193686508","https://openalex.org/W3196328566","https://openalex.org/W3202459445","https://openalex.org/W4226321491","https://openalex.org/W4312604533"],"related_works":["https://openalex.org/W2113785214","https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W4299867837","https://openalex.org/W4386075737","https://openalex.org/W2951583186","https://openalex.org/W1974260915","https://openalex.org/W4382141741","https://openalex.org/W2088028039","https://openalex.org/W3165753266"],"abstract_inverted_index":{"In":[0,47],"the":[1,85,96,106,124],"realm":[2],"of":[3,87,108,126],"category-level":[4,127],"6D":[5,128],"object":[6,129],"pose":[7,28,130],"estimation,":[8],"canonical":[9,89],"3D":[10],"representation":[11],"reconstruction":[12,21],"is":[13,81],"pivotal,":[14],"yet":[15],"current":[16,27],"methods":[17],"show":[18],"limitations":[19],"in":[20,26,44,123],"quality,":[22],"a":[23,51,56,67,120],"key":[24],"step":[25],"estimation":[29],"pipeline.":[30],"To":[31],"address":[32],"this,":[33],"we":[34],"introduce":[35],"an":[36],"innovative":[37],"Adversarial":[38],"Canonical":[39],"Representation":[40],"Reconstruction":[41,69],"Network":[42],"(ACR-Pose)":[43],"this":[45],"paper.":[46],"particular,":[48],"ACR-Pose":[49],"comprises":[50],"Reconstructor,":[52],"with":[53,115],"novel":[54],"sub-modules:":[55],"Pose-Irrelevant":[57],"Module":[58,70],"(PIM)":[59],"for":[60,72],"robustness":[61],"to":[62,83],"rotation":[63],"and":[64,66,99,111],"translation,":[65],"Relational":[68],"(RRM)":[71],"extracting":[73],"relational":[74],"information":[75],"between":[76],"input":[77],"modalities.":[78],"A":[79],"Discriminator":[80],"incorporated":[82],"guide":[84],"generation":[86],"realistic":[88],"representations":[90],"through":[91],"adversarial":[92],"optimization.":[93],"Evaluated":[94],"on":[95],"prevalent":[97],"NOCS-CAMERA":[98],"NOCS-REAL":[100],"datasets,":[101],"our":[102],"method":[103],"significantly":[104],"improves":[105],"performance":[107,114],"baseline":[109],"models":[110],"achieves":[112],"comparable":[113],"existing":[116],"state-of-the-art":[117],"methods,":[118],"representing":[119],"promising":[121],"advancement":[122],"field":[125],"estimation.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}