{"id":"https://openalex.org/W4413146414","doi":"https://doi.org/10.1109/cvpr52734.2025.01244","title":"Eval3D: Interpretable and Fine-Grained Evaluation for 3D Generation","display_name":"Eval3D: Interpretable and Fine-Grained Evaluation for 3D Generation","publication_year":2025,"publication_date":"2025-06-10","ids":{"openalex":"https://openalex.org/W4413146414","doi":"https://doi.org/10.1109/cvpr52734.2025.01244"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52734.2025.01244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52734.2025.01244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5032382984","display_name":"Shivam Duggal","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shivam Duggal","raw_affiliation_strings":["Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069782842","display_name":"Yushi Hu","orcid":"https://orcid.org/0000-0002-7540-2413"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yushi Hu","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055954384","display_name":"Oscar Michel","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oscar Michel","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018421415","display_name":"Aniruddha Kembhavi","orcid":"https://orcid.org/0000-0002-7608-7443"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aniruddha Kembhavi","raw_affiliation_strings":["Wayve"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wayve","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103175123","display_name":"William T. Freeman","orcid":"https://orcid.org/0000-0002-3316-4007"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William T. Freeman","raw_affiliation_strings":["Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088517824","display_name":"Noah A. Smith","orcid":"https://orcid.org/0000-0002-2310-6380"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Noah A. Smith","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032451496","display_name":"Ranjay Krishna","orcid":"https://orcid.org/0000-0001-8784-2531"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ranjay Krishna","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085020955","display_name":"Antonio Torralba","orcid":"https://orcid.org/0000-0003-4915-0256"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Antonio Torralba","raw_affiliation_strings":["Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026171268","display_name":"Ali Farhadi","orcid":"https://orcid.org/0000-0002-0996-0644"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Farhadi","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108727724","display_name":"Wei-Chiu Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei-Chiu Ma","raw_affiliation_strings":["Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.509,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.94579965,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"13326","last_page":"13336"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9023000001907349,"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"}},"topics":[{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9023000001907349,"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/computer-science","display_name":"Computer science","score":0.6073397994041443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4103715717792511}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6073397994041443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4103715717792511}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52734.2025.01244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52734.2025.01244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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":26,"referenced_works":["https://openalex.org/W2229412420","https://openalex.org/W2963627347","https://openalex.org/W2963926543","https://openalex.org/W2986615800","https://openalex.org/W3108645709","https://openalex.org/W3153469116","https://openalex.org/W3168379563","https://openalex.org/W3203887644","https://openalex.org/W3204455502","https://openalex.org/W4200150166","https://openalex.org/W4312708649","https://openalex.org/W4312933868","https://openalex.org/W4313041309","https://openalex.org/W4385318467","https://openalex.org/W4386065887","https://openalex.org/W4386075992","https://openalex.org/W4390873331","https://openalex.org/W4390873542","https://openalex.org/W4390874566","https://openalex.org/W4393248012","https://openalex.org/W4399563855","https://openalex.org/W4402660086","https://openalex.org/W4402727359","https://openalex.org/W4402753913","https://openalex.org/W4402916440","https://openalex.org/W4411119331"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Despite":[0],"the":[1,5,35,38,59,92,128,150,190],"unprecedented":[2],"progress":[3],"in":[4],"field":[6],"of":[7,37,62,94,113,142,152,194],"3D":[8,18,40,49,54,96,114,154,169,183],"generation,":[9,115],"current":[10,195],"systems":[11],"still":[12],"often":[13,57],"fail":[14],"to":[15,148,160],"produce":[16],"high-quality":[17],"assets":[19,64,97,155],"that":[20,88,109],"are":[21],"visually":[22],"appealing":[23],"and":[24,26,119,134,144,172,188,192],"geometrically":[25],"semantically":[27],"consistent":[28],"across":[29,156],"multiple":[30],"viewpoints.":[31],"To":[32],"effectively":[33,124],"assess":[34],"quality":[36,61,93],"generated":[39,63,95,153],"data,":[41],"there":[42],"is":[43,108],"a":[44,47,83,139],"need":[45],"for":[46,74],"reliable":[48],"evaluation":[50,55,86],"tool.":[51],"Unfortunately,":[52],"existing":[53,182],"metrics":[56],"overlook":[58],"geometric":[60,120],"or":[65],"merely":[66],"rely":[67],"on":[68,99],"black-box":[69],"multimodal":[70],"large":[71],"language":[72],"models":[73,133,143,185],"coarse":[75],"assessment.":[76],"In":[77],"this":[78],"paper,":[79],"we":[80],"introduce":[81],"Eval3D,":[82],"fine-grained,":[84],"interpretable":[85],"tool":[87],"can":[89,122],"faithfully":[90],"evaluate":[91,149,181],"based":[98],"various":[100,131],"distinct":[101],"yet":[102],"complementary":[103],"criteria.":[104],"Our":[105],"key":[106],"observation":[107],"many":[110],"desired":[111],"properties":[112],"such":[116],"as":[117,146],"semantic":[118],"consistency,":[121],"be":[123],"captured":[125],"by":[126],"measuring":[127],"consistency":[129],"among":[130],"foundation":[132],"tools.":[135],"We":[136,179],"thus":[137],"leverage":[138],"diverse":[140],"set":[141],"tools":[145],"probes":[147],"inconsistency":[151],"different":[157],"aspects.":[158],"Compared":[159],"prior":[161],"work,":[162],"Eval3D":[163,187],"provides":[164],"pixel-wise":[165],"measurement,":[166],"enables":[167],"accurate":[168],"spatial":[170],"feedback,":[171],"aligns":[173],"more":[174],"closely":[175],"with":[176],"human":[177],"judgments.":[178],"comprehensively":[180],"generation":[184],"using":[186],"highlight":[189],"limitations":[191],"challenges":[193],"models.":[196],"Project":[197],"page:":[198],"http://eval3d.github.io.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-08-24T07:32:12.397491","created_date":"2025-10-10T00:00:00"}
