{"id":"https://openalex.org/W7140306032","doi":"https://doi.org/10.48550/arxiv.2603.22883","title":"Group Editing: Edit Multiple Images in One Go","display_name":"Group Editing: Edit Multiple Images in One Go","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7140306032","doi":"https://doi.org/10.48550/arxiv.2603.22883"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.22883","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22883","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.22883","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130596538","display_name":"Yue Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ma, Yue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130619707","display_name":"Xinyu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xinyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130559677","display_name":"Qianli Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Qianli","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130600751","display_name":"Qinghe Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qinghe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130612090","display_name":"Mingzhe Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Mingzhe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130595386","display_name":"Xiangpeng Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xiangpeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130610660","display_name":"Hao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Hao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130545459","display_name":"Chongbo Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Chongbo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117113485","display_name":"Jixuan Ying","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ying, Jixuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130579856","display_name":"Harry Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Harry","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130613986","display_name":"Hongyu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Hongyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130613148","display_name":"Qifeng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Qifeng","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":12,"corresponding_author_ids":["https://openalex.org/A5130596538"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9107999801635742,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9107999801635742,"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/T11019","display_name":"Image Enhancement Techniques","score":0.007400000002235174,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.007300000172108412,"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/leverage","display_name":"Leverage (statistics)","score":0.6632000207901001},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.49399998784065247},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.484499990940094},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.453900009393692},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4350000023841858},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.414900004863739},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4025000035762787},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3937999904155731},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39239999651908875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7766000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7045000195503235},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6632000207901001},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.49399998784065247},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4596000015735626},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.414900004863739},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4025000035762787},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3937999904155731},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39239999651908875},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.3305000066757202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28679999709129333},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.28369998931884766},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2578999996185303},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2574000060558319},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.22883","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22883","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.22883","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22883","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,60,82,100,131,152,175,194],"tackle":[4],"the":[5,44,79,97,102,110,133,140,183,203],"problem":[6],"of":[7,16,129,205,220],"performing":[8],"consistent":[9,188],"and":[10,33,70,108,161,225],"unified":[11],"modifications":[12,48],"across":[13,43,190],"a":[14,63,76,106,144,155,197],"set":[15],"related":[17],"images.":[18,192],"This":[19],"task":[20],"is":[21],"particularly":[22],"challenging":[23],"because":[24],"these":[25,126],"images":[26,74],"may":[27],"vary":[28],"significantly":[29,214],"in":[30,218],"pose,":[31],"viewpoint,":[32],"spatial":[34,90],"layout.":[35],"Achieving":[36],"coherent":[37],"edits":[38],"requires":[39],"establishing":[40],"reliable":[41],"correspondences":[42,85],"images,":[45],"so":[46],"that":[47,66,212],"can":[49],"be":[50],"applied":[51],"accurately":[52],"to":[53,119,169,186,201],"semantically":[54],"aligned":[55],"regions.":[56],"To":[57,123,148],"address":[58],"this,":[59],"propose":[61],"GroupEditing,":[62],"novel":[64,145],"framework":[65],"builds":[67],"both":[68],"explicit":[69,80,134],"implicit":[71,98],"relationships":[72],"among":[73],"within":[75],"group.":[77],"On":[78,96],"side,":[81,99],"extract":[83],"geometric":[84,135],"using":[86],"VGGT,":[87],"which":[88,181],"provides":[89],"alignment":[91],"based":[92],"on":[93],"visual":[94,221],"features.":[95],"reformulate":[101],"image":[103,166,207],"group":[104],"as":[105],"pseudo-video":[107],"leverage":[109],"temporal":[111],"coherence":[112],"priors":[113],"learned":[114],"by":[115],"pre-trained":[116],"video":[117,141],"models":[118],"capture":[120],"latent":[121],"relationships.":[122],"effectively":[124],"fuse":[125],"two":[127],"types":[128],"correspondences,":[130],"inject":[132],"cues":[136],"from":[137],"VGGT":[138],"into":[139],"model":[142],"through":[143],"fusion":[146],"mechanism.":[147],"support":[149],"large-scale":[150],"training,":[151],"construct":[153],"GroupEditData,":[154],"new":[156],"dataset":[157],"containing":[158],"high-quality":[159],"masks":[160],"detailed":[162],"captions":[163],"for":[164],"numerous":[165],"groups.":[167],"Furthermore,":[168],"ensure":[170],"identity":[171],"preservation":[172],"during":[173],"editing,":[174],"introduce":[176],"an":[177],"alignment-enhanced":[178],"RoPE":[179],"module,":[180],"improves":[182],"model's":[184],"ability":[185],"maintain":[187],"appearance":[189],"multiple":[191],"Finally,":[193],"present":[195],"GroupEditBench,":[196],"dedicated":[198],"benchmark":[199],"designed":[200],"evaluate":[202],"effectiveness":[204],"group-level":[206],"editing.":[208],"Extensive":[209],"experiments":[210],"demonstrate":[211],"GroupEditing":[213],"outperforms":[215],"existing":[216],"methods":[217],"terms":[219],"quality,":[222],"cross-view":[223],"consistency,":[224],"semantic":[226],"alignment.":[227]},"counts_by_year":[],"updated_date":"2026-03-28T06:11:35.319607","created_date":"2026-03-26T00:00:00"}