{"id":"https://openalex.org/W4386598488","doi":"https://doi.org/10.1109/icip49359.2023.10222579","title":"Improving Video Colorization by Test-Time Tuning","display_name":"Improving Video Colorization by Test-Time Tuning","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4386598488","doi":"https://doi.org/10.1109/icip49359.2023.10222579"},"language":"en","primary_location":{"id":"doi:10.1109/icip49359.2023.10222579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip49359.2023.10222579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","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/A5005262130","display_name":"Yaping Zhao","orcid":"https://orcid.org/0000-0002-3482-0942"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yaping Zhao","raw_affiliation_strings":["The University of Hong Kong,Pokfulam,Hong Kong SAR","The University of Hong Kong, Pokfulam, Hong Kong SAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Pokfulam,Hong Kong SAR","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"The University of Hong Kong, Pokfulam, Hong Kong SAR","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016267591","display_name":"Haitian Zheng","orcid":"https://orcid.org/0000-0003-0415-1765"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haitian Zheng","raw_affiliation_strings":["University of Rochester,USA","University of Rochester, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rochester,USA","institution_ids":["https://openalex.org/I5388228"]},{"raw_affiliation_string":"University of Rochester, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055469774","display_name":"Jiebo Luo","orcid":"https://orcid.org/0000-0002-4516-9729"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiebo Luo","raw_affiliation_strings":["University of Rochester,USA","University of Rochester, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rochester,USA","institution_ids":["https://openalex.org/I5388228"]},{"raw_affiliation_string":"University of Rochester, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008832723","display_name":"Edmund Y. Lam","orcid":"https://orcid.org/0000-0001-6268-950X"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Edmund Y. Lam","raw_affiliation_strings":["The University of Hong Kong,Pokfulam,Hong Kong SAR","The University of Hong Kong, Pokfulam, Hong Kong SAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Pokfulam,Hong Kong SAR","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"The University of Hong Kong, Pokfulam, Hong Kong SAR","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"166","last_page":"170"},"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":0.9987000226974487,"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":0.9987000226974487,"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":0.9941999912261963,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9926999807357788,"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/overfitting","display_name":"Overfitting","score":0.8964880704879761},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8459450006484985},{"id":"https://openalex.org/keywords/monochrome","display_name":"Monochrome","score":0.758892297744751},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6534016728401184},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6144432425498962},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5853286981582642},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4676484763622284},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41570937633514404},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.394331693649292},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36859390139579773},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33123379945755005},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06781914830207825}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8964880704879761},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8459450006484985},{"id":"https://openalex.org/C2776754580","wikidata":"https://www.wikidata.org/wiki/Q10770146","display_name":"Monochrome","level":2,"score":0.758892297744751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6534016728401184},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6144432425498962},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5853286981582642},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4676484763622284},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41570937633514404},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.394331693649292},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36859390139579773},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33123379945755005},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06781914830207825},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip49359.2023.10222579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip49359.2023.10222579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322170","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2010981316","https://openalex.org/W2133665775","https://openalex.org/W2603351312","https://openalex.org/W2809852002","https://openalex.org/W2931764303","https://openalex.org/W2953334512","https://openalex.org/W2963426332","https://openalex.org/W2979841973","https://openalex.org/W2989277455","https://openalex.org/W3034832575","https://openalex.org/W3089503240","https://openalex.org/W3098620092","https://openalex.org/W3171519093","https://openalex.org/W4210445907","https://openalex.org/W4225691633","https://openalex.org/W4230012894","https://openalex.org/W4285530677","https://openalex.org/W4286955643","https://openalex.org/W4308236036","https://openalex.org/W4312686620","https://openalex.org/W4319586733","https://openalex.org/W6631190155","https://openalex.org/W6840701391"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W2356040864","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2623088128","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W294870043","https://openalex.org/W3099765033"],"abstract_inverted_index":{"With":[0],"the":[1,27,34,67,93],"advancements":[2],"in":[3,87],"deep":[4],"learning,":[5],"video":[6,20,60],"colorization":[7,61],"by":[8],"propagating":[9],"color":[10],"information":[11],"from":[12,32],"a":[13,18,79],"colorized":[14],"reference":[15,68],"frame":[16],"to":[17,40,58,69,92],"monochrome":[19],"sequence":[21],"has":[22],"been":[23],"well":[24],"explored.":[25],"However,":[26],"existing":[28],"approaches":[29],"often":[30],"suffer":[31],"overfitting":[33],"training":[35,72],"dataset":[36],"and":[37],"sequentially":[38],"lead":[39],"suboptimal":[41],"performance":[42,80],"on":[43,89],"colorizing":[44],"testing":[45],"samples.":[46],"To":[47],"address":[48],"this":[49],"issue,":[50],"we":[51],"propose":[52],"an":[53],"effective":[54],"method,":[55],"which":[56],"aims":[57],"enhance":[59],"through":[62],"test-time":[63],"tuning.":[64],"By":[65],"exploiting":[66],"construct":[70],"additional":[71],"samples":[73],"during":[74],"testing,":[75],"our":[76],"approach":[77],"achieves":[78],"boost":[81],"of":[82],"1":[83],"\u223c":[84],"3":[85],"dB":[86],"PSNR":[88],"average":[90],"compared":[91],"baseline.":[94],"Code":[95],"is":[96],"available":[97],"at:":[98],"https://github.com/IndigoPurple/T3.":[99]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}