{"id":"https://openalex.org/W4415537155","doi":"https://doi.org/10.1145/3746027.3755335","title":"TASR: Timestep-Aware Diffusion Model for Image Super-Resolution","display_name":"TASR: Timestep-Aware Diffusion Model for Image Super-Resolution","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415537155","doi":"https://doi.org/10.1145/3746027.3755335"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755335","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755335","pdf_url":null,"source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3746027.3755335","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Qinwei Lin","orcid":"https://orcid.org/0009-0005-2844-3262"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qinwei Lin","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0005-2844-3262","affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiaopeng Sun","orcid":"https://orcid.org/0009-0008-7583-4428"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaopeng Sun","raw_affiliation_strings":["Meituan Inc., Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0008-7583-4428","affiliations":[{"raw_affiliation_string":"Meituan Inc., Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044844068","display_name":"Yu Gao","orcid":"https://orcid.org/0000-0002-1680-9782"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Gao","raw_affiliation_strings":["Meituan Inc., Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-1680-9782","affiliations":[{"raw_affiliation_string":"Meituan Inc., Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026578419","display_name":"Yujie Zhong","orcid":"https://orcid.org/0000-0001-7113-1022"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yujie Zhong","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7113-1022","affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zheng Zhao","orcid":"https://orcid.org/0009-0003-2354-2240"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Zhao","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-2354-2240","affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084583022","display_name":"Dengjie Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dengjie Li","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-1444-8313","affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028229824","display_name":"Haoqian Wang","orcid":"https://orcid.org/0000-0003-2792-8469"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoqian Wang","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2792-8469","affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.1332,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83503413,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"10034","last_page":"10043"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9983999729156494,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9975000023841858,"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/diffusion","display_name":"Diffusion","score":0.6991999745368958},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6643000245094299},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5875999927520752},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5293999910354614},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.51910001039505},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.517799973487854},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.49779999256134033},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4399000108242035}],"concepts":[{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.6991999745368958},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6643000245094299},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6434000134468079},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5964999794960022},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5875999927520752},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5472999811172485},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5293999910354614},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.51910001039505},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.517799973487854},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.49779999256134033},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4399000108242035},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.40959998965263367},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.3788999915122986},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3758000135421753},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3709999918937683},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.3582000136375427},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.35190001130104065},{"id":"https://openalex.org/C2983568541","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Information transmission","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.2874999940395355},{"id":"https://openalex.org/C68710425","wikidata":"https://www.wikidata.org/wiki/Q5275442","display_name":"Diffusion process","level":3,"score":0.2831000089645386},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.2612000107765198}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755335","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755335","pdf_url":null,"source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3746027.3755335","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755335","pdf_url":null,"source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7636710225","display_name":null,"funder_award_id":"2022YFB36066","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2133665775","https://openalex.org/W2739757502","https://openalex.org/W2741137940","https://openalex.org/W3096831136","https://openalex.org/W4400524387","https://openalex.org/W4404533930"],"related_works":[],"abstract_inverted_index":{"Diffusion":[0,73],"models":[1],"have":[2],"recently":[3],"achieved":[4],"outstanding":[5],"results":[6],"in":[7,83,104],"the":[8,28,38,45,49,70,78,84,95,99,105,110,142],"field":[9],"of":[10,31,48,80,87,98,112,144],"image":[11,91],"super-resolution.":[12],"These":[13],"methods":[14],"typically":[15],"inject":[16],"low-resolution":[17],"(LR)":[18],"images":[19,42],"via":[20],"ControlNet.":[21],"In":[22],"this":[23,53,117],"paper,":[24],"we":[25,55,119],"first":[26],"explore":[27],"temporal":[29],"dynamics":[30],"information":[32,82],"infusion":[33],"through":[34],"ControlNet,":[35],"revealing":[36],"that":[37,62,125],"input":[39],"from":[40,66],"LR":[41,81],"predominantly":[43],"influences":[44],"initial":[46],"stages":[47,86,107],"denoising":[50],"process.":[51],"Leveraging":[52],"insight,":[54],"introduce":[56],"a":[57,121],"novel":[58],"timestep-aware":[59,122],"diffusion":[60,88],"model":[61,101],"adaptively":[63],"integrates":[64],"features":[65],"both":[67],"ControlNet":[68],"and":[69,93,132],"pre-trained":[71],"Stable":[72],"(SD).":[74],"Our":[75],"method":[76],"enhances":[77],"transmission":[79],"early":[85],"to":[89,108],"guarantee":[90],"fidelity":[92],"stimulates":[94],"generation":[96],"ability":[97],"SD":[100],"itself":[102],"more":[103],"later":[106],"enhance":[109],"detail":[111],"generated":[113],"images.":[114],"To":[115],"train":[116],"method,":[118],"propose":[120],"training":[123],"strategy":[124],"adopts":[126],"distinct":[127],"losses":[128],"at":[129],"varying":[130],"timesteps":[131],"acts":[133],"on":[134,138],"disparate":[135],"modules.":[136],"Experiments":[137],"benchmark":[139],"datasets":[140],"demonstrate":[141],"effectiveness":[143],"our":[145],"method.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-25T00:00:00"}