{"id":"https://openalex.org/W4415089170","doi":"https://doi.org/10.1145/3746027.3755291","title":"SAM-TTT: Segment Anything Model via Reverse Parameter Configuration and Test-Time Training for Camouflaged Object Detection","display_name":"SAM-TTT: Segment Anything Model via Reverse Parameter Configuration and Test-Time Training for Camouflaged Object Detection","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415089170","doi":"https://doi.org/10.1145/3746027.3755291"},"language":"en","primary_location":{"id":"doi:10.1145/3746027.3755291","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755291","pdf_url":null,"source":null,"license":null,"license_id":null,"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":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.11884","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101262105","display_name":"Zhenni Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenni Yu","raw_affiliation_strings":["College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, Zhejiang, China and College of Computer Science and Technology, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, Zhejiang, China and College of Computer Science and Technology, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I146620803"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Li Zhao","orcid":"https://orcid.org/0000-0001-5787-2705"},"institutions":[{"id":"https://openalex.org/I4210127700","display_name":"Zhejiang Shuren University","ror":"https://ror.org/0331z5r71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210127700"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhao","raw_affiliation_strings":["College of Information Science and Technology, Zhejiang Shuren University, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Zhejiang Shuren University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I4210127700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050524397","display_name":"Guobao Xiao","orcid":"https://orcid.org/0000-0003-2928-8100"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guobao Xiao","raw_affiliation_strings":["College of Computer Science and Technology, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100699785","display_name":"Xiaoqin Zhang","orcid":"https://orcid.org/0000-0003-0958-7285"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqin Zhang","raw_affiliation_strings":["College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, Zhejiang, China","institution_ids":["https://openalex.org/I146620803"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101262105"],"corresponding_institution_ids":["https://openalex.org/I146620803"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2751851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4030","last_page":"4038"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T11019","display_name":"Image Enhancement Techniques","score":0.9943000078201294,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9883000254631042,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7264999747276306},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.7020000219345093},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6541000008583069},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5789999961853027},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5637000203132629},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.501800000667572},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.48100000619888306},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4514000117778778}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7283999919891357},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7264999747276306},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.7020000219345093},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6541000008583069},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5789999961853027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5698999762535095},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5637000203132629},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.501800000667572},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4514000117778778},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4431999921798706},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4081000089645386},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39430001378059387},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.3598000109195709},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2540000081062317},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.25369998812675476}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3746027.3755291","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755291","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2509.11884","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.11884","pdf_url":"https://arxiv.org/pdf/2509.11884","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2509.11884","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.11884","pdf_url":"https://arxiv.org/pdf/2509.11884","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7439331195","display_name":null,"funder_award_id":"2024YFC3306902","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8934741661","display_name":null,"funder_award_id":"U24A20242, 62475241, 62472312","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"a":[3,48,87,124,177],"new":[4,125,178],"Segment":[5],"Anything":[6],"Model":[7],"(SAM)":[8],"that":[9,58,169],"leverages":[10],"reverse":[11],"parameter":[12],"configuration":[13],"and":[14,43,135],"test-time":[15],"training":[16],"to":[17,55,78,103],"enhance":[18],"its":[19,45],"performance":[20],"on":[21,36,95,164],"Camouflaged":[22],"Object":[23],"Detection":[24],"(COD),":[25],"named":[26],"SAM-TTT.":[27],"While":[28],"most":[29],"existing":[30],"SAM-based":[31],"COD":[32,159,166],"models":[33],"primarily":[34],"focus":[35],"enhancing":[37],"SAM":[38,72],"by":[39,90,107,132],"extracting":[40],"favorable":[41],"features":[42],"amplifying":[44],"advantageous":[46,105,151],"parameters,":[47],"crucial":[49],"gap":[50],"is":[51,76,101],"identified:":[52],"insufficient":[53],"attention":[54],"adverse":[56,84,147],"parameters":[57,85,106,148],"impair":[59],"SAM's":[60,92,155],"semantic":[61,156],"understanding":[62,157],"in":[63,86,158,180],"downstream":[64],"tasks.":[65,119],"To":[66],"tackle":[67],"this":[68,96],"issue,":[69],"the":[70,81,98,170,181],"Reverse":[71],"Parameter":[73],"Configuration":[74],"Module":[75,100],"proposed":[77,171],"effectively":[79],"mitigate":[80],"influence":[82],"of":[83,127],"train-free":[88],"manner":[89],"configuring":[91],"parameters.":[93],"Building":[94],"foundation,":[97],"T-Visioner":[99],"unveiled":[102],"strengthen":[104],"integrating":[108,141],"Test-Time":[109,120],"Training":[110,121],"layers,":[111],"originally":[112],"developed":[113],"for":[114],"language":[115],"tasks,":[116],"into":[117],"vision":[118],"layers":[122,130],"represent":[123],"class":[126],"sequence":[128],"modeling":[129],"characterized":[131],"linear":[133],"complexity":[134],"an":[136],"expressive":[137],"hidden":[138],"state.":[139],"By":[140],"two":[142],"modules,":[143],"SAM-TTT":[144],"simultaneously":[145],"suppresses":[146],"while":[149],"reinforcing":[150],"ones,":[152],"significantly":[153],"improving":[154],"task.":[160],"Our":[161],"experimental":[162],"results":[163],"various":[165],"benchmarks":[167],"demonstrate":[168],"approach":[172],"achieves":[173],"state-of-the-art":[174],"performance,":[175],"setting":[176],"benchmark":[179],"field.":[182],"The":[183],"code":[184],"will":[185],"be":[186],"available":[187],"at":[188],"https://github.com/guobaoxiao/SAM-TTT.":[189]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-12T00:00:00"}
