{"id":"https://openalex.org/W4405934988","doi":"https://doi.org/10.1109/tpami.2024.3519674","title":"Glissando-Net: Deep Single View Category Level Pose Estimation and 3D Reconstruction","display_name":"Glissando-Net: Deep Single View Category Level Pose Estimation and 3D Reconstruction","publication_year":2024,"publication_date":"2024-12-31","ids":{"openalex":"https://openalex.org/W4405934988","doi":"https://doi.org/10.1109/tpami.2024.3519674","pmid":"https://pubmed.ncbi.nlm.nih.gov/40030789"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2024.3519674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3519674","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":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2501.14896","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Bo Sun","orcid":"https://orcid.org/0000-0002-9259-6299"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Sun","raw_affiliation_strings":["Adobe Inc, San Jose, CA, USA","Adobe Inc, San Jose, California"],"raw_orcid":"https://orcid.org/0000-0002-9259-6299","affiliations":[{"raw_affiliation_string":"Adobe Inc, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]},{"raw_affiliation_string":"Adobe Inc, San Jose, California","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083511236","display_name":"Hao Kang","orcid":"https://orcid.org/0000-0002-4238-2153"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Kang","raw_affiliation_strings":["ByteDance Inc., Bellevue, WA, USA","ByteDance Inc., Bellevue, Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ByteDance Inc., Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210108985"]},{"raw_affiliation_string":"ByteDance Inc., Bellevue, Washington","institution_ids":["https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Li Guan","orcid":"https://orcid.org/0000-0001-5094-7970"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Guan","raw_affiliation_strings":["Meta Reality Labs, Menlo Park, CA, USA","Meta Reality Labs, Menlo Park, California"],"raw_orcid":"https://orcid.org/0000-0001-5094-7970","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210128585"]},{"raw_affiliation_string":"Meta Reality Labs, Menlo Park, California","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104097507","display_name":"Haoxiang Li","orcid":"https://orcid.org/0000-0002-8838-8227"},"institutions":[{"id":"https://openalex.org/I174135032","display_name":"Bellevue College","ror":"https://ror.org/05gr4yv49","country_code":"US","type":"education","lineage":["https://openalex.org/I174135032"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haoxiang Li","raw_affiliation_strings":["Pixocial Technology, Bellevue, WA, USA","Pixocial Technology, Bellevue, Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pixocial Technology, Bellevue, WA, USA","institution_ids":["https://openalex.org/I174135032"]},{"raw_affiliation_string":"Pixocial Technology, Bellevue, Washington","institution_ids":["https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024073593","display_name":"Philippos Mordohai","orcid":"https://orcid.org/0000-0002-9671-4408"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philippos Mordohai","raw_affiliation_strings":["Stevens Institute of Technology, Hoboken, NJ, USA","Stevens Institute of Technology, Hoboken, New Jersey"],"raw_orcid":"https://orcid.org/0000-0002-9671-4408","affiliations":[{"raw_affiliation_string":"Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]},{"raw_affiliation_string":"Stevens Institute of Technology, Hoboken, New Jersey","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081114810","display_name":"Gang Hua","orcid":"https://orcid.org/0000-0001-9522-6157"},"institutions":[{"id":"https://openalex.org/I174135032","display_name":"Bellevue College","ror":"https://ror.org/05gr4yv49","country_code":"US","type":"education","lineage":["https://openalex.org/I174135032"]},{"id":"https://openalex.org/I4210093996","display_name":"Dolby (United States)","ror":"https://ror.org/01eyenr26","country_code":"US","type":"company","lineage":["https://openalex.org/I4210093996"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Hua","raw_affiliation_strings":["Dolby Laboratories, Bellevue, WA, USA","Dolby Laboratories, Bellevue, Washington"],"raw_orcid":"https://orcid.org/0000-0001-9522-6157","affiliations":[{"raw_affiliation_string":"Dolby Laboratories, Bellevue, WA, USA","institution_ids":["https://openalex.org/I174135032","https://openalex.org/I4210093996"]},{"raw_affiliation_string":"Dolby Laboratories, Bellevue, Washington","institution_ids":["https://openalex.org/I4210093996","https://openalex.org/I4210108985"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6006,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64824265,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"47","issue":"4","first_page":"2298","last_page":"2312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9977999925613403,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8052535057067871},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8052152395248413},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7593410015106201},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6814867258071899},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6256005167961121},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5871610045433044},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5576509833335876},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5304362773895264},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.49117419123649597},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4623417258262634},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45537716150283813},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.45301276445388794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33122220635414124}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8052535057067871},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8052152395248413},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7593410015106201},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6814867258071899},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6256005167961121},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5871610045433044},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5576509833335876},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5304362773895264},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.49117419123649597},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4623417258262634},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45537716150283813},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.45301276445388794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33122220635414124},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2024.3519674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3519674","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:40030789","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40030789","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},{"id":"pmh:oai:arXiv.org:2501.14896","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.14896","pdf_url":"https://arxiv.org/pdf/2501.14896","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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2501.14896","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.14896","pdf_url":"https://arxiv.org/pdf/2501.14896","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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6358036060","display_name":null,"funder_award_id":"IIS-1527294","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7636847868","display_name":null,"funder_award_id":"IIS-1637761","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4405934988.pdf"},"referenced_works_count":79,"referenced_works":["https://openalex.org/W1893912098","https://openalex.org/W1901129140","https://openalex.org/W1946609740","https://openalex.org/W1969868017","https://openalex.org/W2046249243","https://openalex.org/W2196978909","https://openalex.org/W2342277278","https://openalex.org/W2400577036","https://openalex.org/W2468368736","https://openalex.org/W2472269674","https://openalex.org/W2488101876","https://openalex.org/W2560544142","https://openalex.org/W2560722161","https://openalex.org/W2574567538","https://openalex.org/W2768879211","https://openalex.org/W2888752296","https://openalex.org/W2903435684","https://openalex.org/W2905288042","https://openalex.org/W2962778872","https://openalex.org/W2962783853","https://openalex.org/W2962912205","https://openalex.org/W2962988048","https://openalex.org/W2963150697","https://openalex.org/W2963177347","https://openalex.org/W2963188159","https://openalex.org/W2963453931","https://openalex.org/W2963706662","https://openalex.org/W2963739349","https://openalex.org/W2963756608","https://openalex.org/W2963850211","https://openalex.org/W2963892972","https://openalex.org/W2964249569","https://openalex.org/W2980925180","https://openalex.org/W2981081013","https://openalex.org/W2981390381","https://openalex.org/W2984163771","https://openalex.org/W2987505621","https://openalex.org/W2989915422","https://openalex.org/W2990578762","https://openalex.org/W2991202319","https://openalex.org/W2993195924","https://openalex.org/W2997687993","https://openalex.org/W3009153702","https://openalex.org/W3009516594","https://openalex.org/W3023751841","https://openalex.org/W3025800305","https://openalex.org/W3034573608","https://openalex.org/W3034597466","https://openalex.org/W3034712732","https://openalex.org/W3034899291","https://openalex.org/W3034964128","https://openalex.org/W3035268949","https://openalex.org/W3035269921","https://openalex.org/W3035355652","https://openalex.org/W3035424742","https://openalex.org/W3035499195","https://openalex.org/W3036421240","https://openalex.org/W3091357794","https://openalex.org/W3106569148","https://openalex.org/W3107372911","https://openalex.org/W3108671865","https://openalex.org/W3108776058","https://openalex.org/W3173617232","https://openalex.org/W3175844808","https://openalex.org/W3180720907","https://openalex.org/W3196328566","https://openalex.org/W4250482878","https://openalex.org/W4250952223","https://openalex.org/W4312801317","https://openalex.org/W6687484953","https://openalex.org/W6687718950","https://openalex.org/W6729687604","https://openalex.org/W6739778489","https://openalex.org/W6745947945","https://openalex.org/W6755143522","https://openalex.org/W6756498474","https://openalex.org/W6764941374","https://openalex.org/W6783432159","https://openalex.org/W6803231713"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W4320086129"],"abstract_inverted_index":{"We":[0,68,170],"present":[1],"a":[2,25,78,92,240],"deep":[3],"learning":[4],"model,":[5],"dubbed":[6],"Glissando-Net,":[7],"to":[8,76,162,182,185,189],"simultaneously":[9],"estimate":[10],"the":[11,15,21,39,63,83,89,101,105,116,132,138,141,149,152,159,164,173,190,198,201,236,246,249,265,275],"pose":[12,87,136,226,238,241],"and":[13,62,86,109,126,135,178,228,233,239,259,271],"reconstruct":[14],"3D":[16,84,133,153,202,219,243],"shape":[17,85,134,229],"of":[18,51,82,88,104,137,200,209,221,231,248,267],"objects":[19],"at":[20,38],"category":[22],"level":[23],"from":[24,115],"single":[26,93],"RGB":[27,60,94,177],"image.":[28],"Previous":[29],"works":[30],"predominantly":[31],"focused":[32],"on":[33,225],"either":[34],"estimating":[35],"poses":[36],"(often":[37],"instance":[40],"level),":[41],"or":[42],"reconstructing":[43],"shapes,":[44],"but":[45],"not":[46],"both.":[47],"Glissando-Net":[48,75,210],"is":[49,205,211],"composed":[50],"two":[52,70,174],"auto-encoders":[53],"that":[54],"are":[55],"jointly":[56,171],"trained,":[57],"one":[58],"for":[59,65,166,176],"images":[61],"other":[64],"point":[66,106,154,179,191,203],"clouds.":[67],"embrace":[69],"key":[71],"design":[72,208],"choices":[73],"in":[74,123,140,151,158],"achieve":[77],"more":[79,167],"accurate":[80,168],"prediction":[81],"object":[90,139,237],"given":[91],"image":[95,117],"as":[96],"input.":[97],"First,":[98],"we":[99,129,146,223],"augment":[100],"feature":[102,113],"maps":[103,114],"cloud":[107,180,192,204],"encoder":[108,199],"decoder":[110,142,193],"with":[111,261,274],"transformed":[112],"decoder,":[118],"enabling":[119],"effective":[120],"2D-3D":[121],"interaction":[122],"both":[124,131,256],"training":[125,160],"prediction.":[127,169],"Second,":[128],"predict":[130,235],"stage.":[143],"This":[144],"way,":[145],"better":[147],"utilize":[148],"information":[150],"clouds":[155],"presented":[156],"only":[157],"stage":[161],"train":[163,172],"network":[165],"encoder-decoders":[175],"data":[181],"learn":[183],"how":[184],"pass":[186],"latent":[187],"features":[188],"during":[194],"inference.":[195],"In":[196],"testing,":[197],"discarded.":[206],"The":[207],"inspired":[212],"by":[213],"codeSLAM.":[214],"Unlike":[215],"codeSLAM,":[216],"which":[217],"targets":[218],"reconstruction":[220,230,244],"scenes,":[222],"focus":[224],"estimation":[227],"objects,":[232],"directly":[234],"invariant":[242],"without":[245],"need":[247],"code":[250],"optimization":[251],"step.":[252],"Extensive":[253],"experiments,":[254],"involving":[255],"ablation":[257],"studies":[258],"comparison":[260],"competing":[262],"methods,":[263],"demonstrate":[264],"efficacy":[266],"our":[268],"proposed":[269],"method,":[270],"compare":[272],"favorably":[273],"state-of-the-art.":[276]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
