{"id":"https://openalex.org/W7166521593","doi":"https://doi.org/10.48550/arxiv.2606.28094","title":"OSOR: One-Step Diffusion Inpainting for Effect-Aware Object Removal","display_name":"OSOR: One-Step Diffusion Inpainting for Effect-Aware Object Removal","publication_year":2026,"publication_date":"2026-06-26","ids":{"openalex":"https://openalex.org/W7166521593","doi":"https://doi.org/10.48550/arxiv.2606.28094"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.28094","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28094","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.28094","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011333342","display_name":"Qinming Zhou","orcid":"https://orcid.org/0000-0001-6211-0588"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Qinming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139601444","display_name":"Chenxi Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Chenxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139567327","display_name":"Deyang Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Deyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139575602","display_name":"Junhao He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Junhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004010230","display_name":"X W Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Xiangheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077655839","display_name":"Peike Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Peike","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113485823","display_name":"H. Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Haotian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013728469","display_name":"Leilei Cao","orcid":"https://orcid.org/0000-0003-0336-9295"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Leilei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139574275","display_name":"Linfeng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Linfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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":0.8302000164985657,"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":0.8302000164985657,"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":0.040800001472234726,"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":0.03400000184774399,"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/pipeline","display_name":"Pipeline (software)","score":0.7299000024795532},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6909999847412109},{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.6335999965667725},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.590499997138977},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5794000029563904},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5077000260353088},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.45010000467300415},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4300000071525574}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7405999898910522},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7299000024795532},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6909999847412109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6901999711990356},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6833000183105469},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.6335999965667725},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.590499997138977},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5794000029563904},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5077000260353088},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.45010000467300415},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4300000071525574},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4025000035762787},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3946000039577484},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.38179999589920044},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.37209999561309814},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.32499998807907104},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.3125999867916107},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2678000032901764}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.28094","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28094","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.28094","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28094","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7309470772743225}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Real-world":[0],"object":[1,85],"removal":[2,49,117,153,167],"is":[3],"challenging":[4],"due":[5],"to":[6,23,114,138,161,184],"two":[7],"key":[8],"difficulties:":[9],"the":[10,26,52],"target":[11],"object's":[12],"non-local":[13],"effects,":[14],"such":[15],"as":[16],"shadows":[17],"and":[18,25,40,64,83,126,155,159],"reflections,":[19],"which":[20,78,149],"are":[21,31],"difficult":[22],"model,":[24],"fact":[27],"that":[28,107,133,171],"user-provided":[29],"masks":[30],"often":[32],"inaccurate":[33],"or":[34],"incomplete.":[35],"With":[36],"billions":[37],"of":[38,42,54],"parameters":[39],"tens":[41],"denoising":[43],"steps,":[44],"diffusion-based":[45],"models":[46,113],"achieve":[47],"strong":[48,174],"performance":[50,163],"at":[51,142],"expense":[53],"substantial":[55],"computational":[56],"cost,":[57],"limiting":[58],"their":[59],"use":[60],"in":[61,178],"interactive":[62],"applications":[63],"on":[65,164],"edge":[66],"devices.":[67],"To":[68],"address":[69],"these":[70],"challenges,":[71],"we":[72,146],"present":[73],"OSOR":[74,88,172],"(One-Step":[75],"Object":[76],"Removal),":[77],"simultaneously":[79],"achieves":[80],"efficient,":[81],"effect-aware,":[82],"mask-robust":[84],"removal.":[86],"Concretely,":[87],"introduces:":[89],"(1)":[90],"an":[91,104],"occupancy-guided":[92],"discriminator":[93],"for":[94],"precise":[95],"boundary":[96],"supervision,":[97],"enabling":[98],"stable":[99],"single-step":[100],"diffusion":[101,112,176],"training;":[102],"(2)":[103],"alpha":[105],"head":[106],"leverages":[108],"knowledge":[109],"from":[110],"pretrained":[111],"predict":[115],"appropriate":[116],"regions":[118],"with":[119],"minimal":[120],"overhead,":[121],"thereby":[122],"handling":[123],"imperfect":[124],"masks;":[125],"(3)":[127],"a":[128],"semantic-anchored":[129],"verification":[130],"pipeline":[131],"(SAVP)":[132],"filters":[134],"noisy":[135],"instruction-based":[136],"triplets":[137],"produce":[139],"effect-aware":[140],"supervision":[141],"scale.":[143],"Using":[144],"SAVP,":[145],"curate":[147],"CORNE,":[148],"contains":[150],"280K":[151],"verified":[152],"pairs,":[154],"further":[156],"annotate":[157],"AnimeEraseBench":[158],"TextEraseBench":[160],"evaluate":[162],"more":[165],"complex":[166],"tasks.":[168],"Experiments":[169],"show":[170],"surpasses":[173],"multi-step":[175],"baselines":[177],"perceptual":[179],"quality":[180],"while":[181],"achieving":[182],"$4\\times$":[183],"$30\\times$":[185],"faster":[186],"inference.":[187]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-30T00:00:00"}
