{"id":"https://openalex.org/W7161169209","doi":"https://doi.org/10.1109/dcc66757.2026.00015","title":"Generative Preprocessing for Image Compression with Pre-Trained Diffusion Models","display_name":"Generative Preprocessing for Image Compression with Pre-Trained Diffusion Models","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7161169209","doi":"https://doi.org/10.1109/dcc66757.2026.00015"},"language":null,"primary_location":{"id":"doi:10.1109/dcc66757.2026.00015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dcc66757.2026.00015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 Data Compression Conference (DCC)","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/A5101980608","display_name":"Mengxi Guo","orcid":"https://orcid.org/0009-0007-9490-6661"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mengxi Guo","raw_affiliation_strings":["Bytedance Inc.,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bytedance Inc.,Shenzhen,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136169624","display_name":"Shijie Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shijie Zhao","raw_affiliation_strings":["Bytedance Inc.,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bytedance Inc.,Shenzhen,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136174005","display_name":"Junlin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junlin Li","raw_affiliation_strings":["Bytedance Inc.,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bytedance Inc.,Shenzhen,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5136166123","display_name":"Li Xin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Zhang","raw_affiliation_strings":["Bytedance Inc.,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bytedance Inc.,Shenzhen,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101980608"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94771961,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"73","last_page":"82"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.8123000264167786,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.8123000264167786,"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/T11269","display_name":"Algorithms and Data Compression","score":0.021800000220537186,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11034","display_name":"Digital Filter Design and Implementation","score":0.012799999676644802,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/compression","display_name":"Compression (physics)","score":0.5138999819755554},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49880000948905945},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4287000000476837},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4174000024795532},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.41280001401901245},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.3912999927997589}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.654699981212616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5938000082969666},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.5138999819755554},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5027999877929688},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49880000948905945},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.41280001401901245},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3912999927997589},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.34209999442100525},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.30790001153945923},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3061000108718872},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29249998927116394},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29109999537467957}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dcc66757.2026.00015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dcc66757.2026.00015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 Data Compression Conference (DCC)","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Preprocessing":[0],"is":[1],"a":[2,24,36,46,58,72,83,87,122],"well-established":[3],"technique":[4],"for":[5,31,41],"optimizing":[6],"compression,":[7],"yet":[8],"existing":[9],"methods":[10],"are":[11],"predominantly":[12],"Rate-Distortion":[13],"(R-D)":[14],"optimized":[15],"and":[16,86,101,111,132],"constrained":[17],"by":[18,82],"pixel-level":[19],"fidelity.":[20],"This":[21],"work":[22],"pioneers":[23],"shift":[25],"towards":[26],"Rate-Perception":[27,84],"(R-P)":[28],"optimization":[29],"by,":[30],"the":[32,52,76,103,129],"first":[33],"time,":[34],"adapting":[35],"large-scale":[37],"pre-trained":[38],"diffusion":[39],"model":[40,62],"compression":[42],"preprocessing.":[43],"We":[44],"propose":[45],"two-stage":[47],"framework:":[48],"first,":[49],"we":[50,70],"distill":[51],"multi-step":[53],"Stable":[54],"Diffusion":[55],"2.1":[56],"into":[57],"compact,":[59],"one-step":[60],"image-to-image":[61],"using":[63],"Consistent":[64],"Score":[65],"Identity":[66],"Distillation":[67],"(CiD).":[68],"Second,":[69],"perform":[71],"parameter-efficient":[73],"fine-tuning":[74],"of":[75],"distilled":[77],"model's":[78,104],"attention":[79],"modules,":[80],"guided":[81],"loss":[85],"differentiable":[88],"codec":[89],"surrogate.":[90],"Our":[91],"method":[92],"seamlessly":[93],"integrates":[94],"with":[95],"standard":[96],"codecs":[97],"without":[98],"any":[99],"modification":[100],"leverages":[102],"powerful":[105],"generative":[106],"priors":[107],"to":[108,121],"enhance":[109],"texture":[110],"mitigate":[112],"artifacts.":[113],"Experiments":[114],"show":[115],"substantial":[116],"R-P":[117],"gains,":[118],"achieving":[119],"up":[120],"30.13%":[123],"BD-rate":[124],"reduction":[125],"in":[126],"DISTS":[127],"on":[128],"Kodak":[130],"dataset":[131],"delivering":[133],"superior":[134],"subjective":[135],"visual":[136],"quality.":[137]},"counts_by_year":[],"updated_date":"2026-05-16T06:04:12.930555","created_date":"2026-05-15T00:00:00"}