{"id":"https://openalex.org/W3091766791","doi":"https://doi.org/10.1109/icra40945.2020.9196953","title":"Pose-guided Auto-Encoder and Feature-Based Refinement for 6-DoF Object Pose Regression","display_name":"Pose-guided Auto-Encoder and Feature-Based Refinement for 6-DoF Object Pose Regression","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3091766791","doi":"https://doi.org/10.1109/icra40945.2020.9196953","mag":"3091766791"},"language":"en","primary_location":{"id":"doi:10.1109/icra40945.2020.9196953","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9196953","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"article","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/A5100363813","display_name":"Zhigang Li","orcid":"https://orcid.org/0000-0003-0464-8800"},"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":true,"raw_author_name":"Zhigang Li","raw_affiliation_strings":["Department of Automation & BNRist, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation & BNRist, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024401174","display_name":"Xiangyang Ji","orcid":"https://orcid.org/0000-0002-7333-9975"},"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":"Xiangyang Ji","raw_affiliation_strings":["Department of Automation & BNRist, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation & BNRist, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100363813"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.4711,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.82193991,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"8397","last_page":"8403"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9987999796867371,"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":0.9987999796867371,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9933000206947327,"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":0.9925000071525574,"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":0.8148781061172485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8131270408630371},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7542088627815247},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6370890140533447},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5887300372123718},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.5541728734970093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5357512831687927},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5047708749771118},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49398714303970337},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4590607285499573},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.44173699617385864},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.42456692457199097},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4171411693096161}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8148781061172485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8131270408630371},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7542088627815247},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6370890140533447},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5887300372123718},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.5541728734970093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5357512831687927},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5047708749771118},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49398714303970337},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4590607285499573},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.44173699617385864},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.42456692457199097},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4171411693096161},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra40945.2020.9196953","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9196953","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","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":52,"referenced_works":["https://openalex.org/W1509114909","https://openalex.org/W1522301498","https://openalex.org/W1526868886","https://openalex.org/W1591870335","https://openalex.org/W1949483711","https://openalex.org/W2083624955","https://openalex.org/W2112206181","https://openalex.org/W2168356304","https://openalex.org/W2200124539","https://openalex.org/W2488101876","https://openalex.org/W2518803647","https://openalex.org/W2570343428","https://openalex.org/W2580726517","https://openalex.org/W2584731199","https://openalex.org/W2600447016","https://openalex.org/W2602709638","https://openalex.org/W2604236302","https://openalex.org/W2605111497","https://openalex.org/W2768879211","https://openalex.org/W2771385090","https://openalex.org/W2795645133","https://openalex.org/W2795999188","https://openalex.org/W2887843334","https://openalex.org/W2895410314","https://openalex.org/W2895439318","https://openalex.org/W2899771611","https://openalex.org/W2922243907","https://openalex.org/W2945685071","https://openalex.org/W2950921159","https://openalex.org/W2952036981","https://openalex.org/W2962783853","https://openalex.org/W2963188159","https://openalex.org/W2963430499","https://openalex.org/W2963756608","https://openalex.org/W2963892972","https://openalex.org/W2964121744","https://openalex.org/W2964249569","https://openalex.org/W2989915422","https://openalex.org/W3009516594","https://openalex.org/W3100052745","https://openalex.org/W3106250896","https://openalex.org/W6630474111","https://openalex.org/W6631190155","https://openalex.org/W6631711059","https://openalex.org/W6735629468","https://openalex.org/W6740978277","https://openalex.org/W6750429153","https://openalex.org/W6752942594","https://openalex.org/W6754838991","https://openalex.org/W6756040250","https://openalex.org/W6762391802","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4287600488","https://openalex.org/W4312694060","https://openalex.org/W4281696776","https://openalex.org/W4318148659","https://openalex.org/W4387967917","https://openalex.org/W4299867837","https://openalex.org/W2951583186"],"abstract_inverted_index":{"Accurately":[0],"estimating":[1],"the":[2,26,46,60,82,89,102,105,120,130],"6-DoF":[3],"object":[4],"pose":[5,19,52,83,103],"from":[6,45,65,104],"a":[7,12,50,135],"single":[8],"RGB":[9],"image":[10,47],"is":[11,28],"challenging":[13],"task":[14],"in":[15],"computer":[16],"vision.":[17],"Though":[18],"regression":[20],"approaches":[21,133],"have":[22],"achieved":[23,116],"great":[24],"progress,":[25],"performance":[27,85,118],"still":[29],"limited.":[30],"In":[31],"this":[32],"work,":[33],"we":[34,94],"propose":[35,95],"Pose-guided":[36],"Auto-Encoder":[37],"(PAE),":[38],"which":[39,100],"can":[40,78],"distill":[41],"better":[42],"pose-related":[43],"features":[44,64,107],"by":[48],"utilizing":[49],"suitable":[51],"representation,":[53],"3D":[54],"Location":[55],"Field":[56],"(3DLF),":[57],"to":[58,70],"guide":[59],"encoding":[61],"process.":[62],"The":[63],"PAE":[66,77,111],"show":[67],"strong":[68],"robustness":[69],"pose-irrelevant":[71],"factors.":[72],"Compared":[73],"with":[74,112,134],"traditional":[75],"auto-encoder,":[76],"not":[79,127],"only":[80,128],"improve":[81],"estimation":[84],"but":[86,138],"also":[87,139],"handle":[88],"ambiguity":[90],"viewpoints":[91],"problem.":[92],"Further,":[93],"Feature-based":[96],"Pose":[97],"Refiner":[98],"(FPR),":[99],"refines":[101],"extracted":[106],"without":[108],"rendering.":[109],"Combining":[110],"FPR,":[113],"our":[114],"approach":[115,126],"state-of-the-art":[117,143],"on":[119],"widely":[121],"used":[122],"LINEMOD":[123],"dataset.":[124],"Our":[125],"outperforms":[129],"direct":[131],"regression-based":[132],"large":[136],"margin":[137],"thrillingly":[140],"surpasses":[141],"current":[142],"indirect":[144],"PnP-based":[145],"approach.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}