{"id":"https://openalex.org/W7131262279","doi":"https://doi.org/10.1109/vcip67698.2025.11396854","title":"CGICM: CLIP-Guided Semantic Frequency Adaptation in Image Compression for Machines","display_name":"CGICM: CLIP-Guided Semantic Frequency Adaptation in Image Compression for Machines","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W7131262279","doi":"https://doi.org/10.1109/vcip67698.2025.11396854"},"language":null,"primary_location":{"id":"doi:10.1109/vcip67698.2025.11396854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip67698.2025.11396854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Visual Communications and Image Processing (VCIP)","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/A5126722376","display_name":"Yongqiang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongqiang Wang","raw_affiliation_strings":["School of Microelectronics Xi’an Jiaotong University,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics Xi’an Jiaotong University,Xi’an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101870782","display_name":"Feng Liang","orcid":"https://orcid.org/0000-0002-6793-5586"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Liang","raw_affiliation_strings":["School of Microelectronics Xi’an Jiaotong University,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics Xi’an Jiaotong University,Xi’an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126738358","display_name":"Heming Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I180203408","display_name":"Yokohama National University","ror":"https://ror.org/03zyp6p76","country_code":"JP","type":"education","lineage":["https://openalex.org/I180203408"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Heming Sun","raw_affiliation_strings":["Faculty of Engineering Yokohama National University,Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering Yokohama National University,Kanagawa,Japan","institution_ids":["https://openalex.org/I180203408"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121502885","display_name":"Jiro Katto","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jiro Katto","raw_affiliation_strings":["School of Fundamental Science and Engineering Waseda University,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"School of Fundamental Science and Engineering Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5126722376"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75314549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9559999704360962,"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":0.9559999704360962,"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":0.007000000216066837,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.005200000014156103,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4652999937534332},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.4472000002861023},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.41429999470710754},{"id":"https://openalex.org/keywords/compression-artifact","display_name":"Compression artifact","score":0.376800000667572},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.376800000667572},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.37059998512268066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3702000081539154},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3522000014781952}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7699999809265137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6780999898910522},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5853000283241272},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.4472000002861023},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.41429999470710754},{"id":"https://openalex.org/C57654395","wikidata":"https://www.wikidata.org/wiki/Q1097775","display_name":"Compression artifact","level":5,"score":0.376800000667572},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.376800000667572},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3431999981403351},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32330000400543213},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C2778192920","wikidata":"https://www.wikidata.org/wiki/Q16874989","display_name":"Signal compression","level":4,"score":0.30480000376701355},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.26510000228881836},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.25780001282691956}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip67698.2025.11396854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip67698.2025.11396854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2108598243","https://openalex.org/W2140196014","https://openalex.org/W2146395539","https://openalex.org/W2194775991","https://openalex.org/W2806070179","https://openalex.org/W3034469748","https://openalex.org/W3186910762","https://openalex.org/W3202918664","https://openalex.org/W3212865599","https://openalex.org/W4387967955","https://openalex.org/W4390872385","https://openalex.org/W4403841811","https://openalex.org/W4406046518","https://openalex.org/W4410478307"],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"deep":[3],"learning-based":[4],"image":[5,22,116],"compression":[6,117],"techniques":[7],"have":[8],"advanced":[9],"rapidly,":[10],"surpassing":[11],"traditional":[12],"methods":[13,34],"in":[14,20,136],"terms":[15],"of":[16,29,48,123],"rate-distortion":[17],"performance.":[18,104],"However,":[19],"machine-oriented":[21],"compression,":[23],"preserving":[24],"high-level":[25],"semantic":[26,49,64],"information":[27,50],"is":[28,108],"greater":[30],"importance.":[31],"Most":[32],"existing":[33,114],"employ":[35],"only":[36],"image-level":[37],"prompts":[38],"to":[39,45,96,110],"guide":[40],"frequency":[41,65,71,93],"domain":[42,66],"processing,":[43],"leading":[44],"suboptimal":[46],"preservation":[47],"for":[51],"downstream":[52],"machine":[53,102,138],"vision":[54,139],"tasks.":[55,140],"To":[56],"address":[57],"this":[58],"limitation,":[59],"we":[60],"propose":[61],"a":[62],"CLIP-guided":[63],"adaptation":[67],"module":[68,89],"that":[69,130],"extracts":[70],"features":[72],"by":[73,85],"applying":[74],"both":[75],"the":[76,81,88,92,97,124],"fast":[77],"Fourier":[78],"transform":[79],"and":[80],"wavelet":[82],"transform.":[83],"Guided":[84],"text-based":[86],"semantics,":[87],"further":[90],"enhances":[91],"components":[94],"relevant":[95],"target":[98],"task,":[99],"thereby":[100],"improving":[101],"perception":[103],"The":[105],"proposed":[106],"adapter":[107],"designed":[109],"be":[111],"plug-and-play":[112],"with":[113],"learned":[115],"(LIC)":[118],"models":[119],"without":[120],"requiring":[121],"retraining":[122],"full":[125],"model.":[126],"Experimental":[127],"results":[128],"demonstrate":[129],"our":[131],"method":[132],"outperforms":[133],"state-of-the-art":[134],"approaches":[135],"multiple":[137]},"counts_by_year":[],"updated_date":"2026-02-25T21:11:00.739837","created_date":"2026-02-25T00:00:00"}