{"id":"https://openalex.org/W4415089394","doi":"https://doi.org/10.48550/arxiv.2509.12039","title":"RAM++: Robust Representation Learning via Adaptive Mask for All-in-One Image Restoration","display_name":"RAM++: Robust Representation Learning via Adaptive Mask for All-in-One Image Restoration","publication_year":2025,"publication_date":"2025-09-15","ids":{"openalex":"https://openalex.org/W4415089394","doi":"https://doi.org/10.48550/arxiv.2509.12039"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2509.12039","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.12039","pdf_url":"https://arxiv.org/pdf/2509.12039","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"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.12039","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100353034","display_name":"Zilong Zhang","orcid":"https://orcid.org/0000-0002-7912-3622"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Zilong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078862473","display_name":"Chuwei Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Chujie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086639598","display_name":"Chunle Guo","orcid":"https://orcid.org/0000-0002-2432-2026"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Chunle","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100642156","display_name":"Yong Zhang","orcid":"https://orcid.org/0000-0003-4997-698X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100884245","display_name":"Chao Xue","orcid":"https://orcid.org/0000-0002-9507-9991"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Chao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037131575","display_name":"Ming\u2010Ming Cheng","orcid":"https://orcid.org/0000-0001-5550-8758"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Ming-Ming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034122071","display_name":"Chongyi Li","orcid":"https://orcid.org/0000-0003-2609-2460"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chongyi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100353034"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9878000020980835,"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":0.9878000020980835,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9699000120162964,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9550999999046326,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7401999831199646},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6370000243186951},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5425999760627747},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5328999757766724},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4982999861240387},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.49390000104904175},{"id":"https://openalex.org/keywords/morphing","display_name":"Morphing","score":0.4884999990463257},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48069998621940613},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47780001163482666}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7401999831199646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6949999928474426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6532999873161316},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6370000243186951},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5425999760627747},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4982999861240387},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.49390000104904175},{"id":"https://openalex.org/C50637493","wikidata":"https://www.wikidata.org/wiki/Q1136781","display_name":"Morphing","level":2,"score":0.4884999990463257},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48069998621940613},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47780001163482666},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4684000015258789},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.45719999074935913},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45660001039505005},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.36480000615119934},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3601999878883362},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3456000089645386},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3303000032901764},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2766999900341034},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2509.12039","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.12039","pdf_url":"https://arxiv.org/pdf/2509.12039","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"},{"id":"doi:10.48550/arxiv.2509.12039","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.12039","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2509.12039","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.12039","pdf_url":"https://arxiv.org/pdf/2509.12039","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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,92],"work":[1],"presents":[2],"Robust":[3,141],"Representation":[4],"Learning":[5],"via":[6],"Adaptive":[7,75],"Mask":[8,77,110],"(RAM++),":[9],"a":[10,79,114,145],"two-stage":[11],"framework":[12],"for":[13],"all-in-one":[14],"image":[15,47,103],"restoration.":[16,30,166],"RAM++":[17,49,170],"integrates":[18],"high-level":[19],"semantic":[20],"understanding":[21],"with":[22,46,122,156],"low-level":[23],"texture":[24],"generation":[25],"to":[26,61,67,86,97,125,160],"achieve":[27,161],"content-oriented":[28],"robust":[29],"It":[31],"addresses":[32],"the":[33,95,120,127],"limitations":[34],"of":[35],"existing":[36],"degradation-oriented":[37],"methods":[38],"in":[39],"extreme":[40],"scenarios":[41],"(e.g.,":[42],"degradations":[43],"strongly":[44],"coupled":[45],"structures).":[48],"also":[50],"mitigates":[51],"common":[52],"challenges":[53],"such":[54],"as":[55],"unbalanced":[56],"performance":[57,176],"across":[58,177],"tasks,":[59],"overfitting":[60],"seen":[62],"degradations,":[63],"and":[64,89,102,133,152,163,174,181,186],"weak":[65],"generalization":[66],"unseen":[68],"ones":[69],"through":[70],"three":[71],"key":[72],"designs:":[73],"1)":[74],"Semantic-Aware":[76],"(AdaSAM):":[78],"pretraining":[80,132],"strategy":[81,117,146],"that":[82,118,147],"applies":[83],"pixel-level":[84],"masks":[85],"semantically":[87,150,164],"rich":[88],"textured":[90],"regions.":[91],"design":[93],"enables":[94],"network":[96],"learn":[98],"both":[99],"generative":[100],"priors":[101,105],"content":[104],"from":[106],"various":[107],"degradations.":[108,183],"2)":[109],"Attribute":[111],"Conductance":[112],"(MAC):":[113],"selective":[115],"fine-tuning":[116,135],"adjusts":[119],"layers":[121],"higher":[123],"contributions":[124],"bridge":[126],"integrity":[128],"gap":[129],"between":[130],"masked":[131],"full-image":[134],"while":[136],"retaining":[137],"learned":[138],"priors.":[139],"3)":[140],"Feature":[142],"Regularization":[143],"(RFR):":[144],"leverages":[148],"DINOv2's":[149],"consistent":[151],"degradation-invariant":[153],"representations,":[154],"together":[155],"efficient":[157],"feature":[158],"fusion,":[159],"faithful":[162],"coherent":[165],"With":[167],"these":[168],"designs,":[169],"achieves":[171],"robust,":[172],"well-balanced,":[173],"state-of-the-art":[175],"seen,":[178],"unseen,":[179],"extreme,":[180],"mixed":[182],"Our":[184],"code":[185],"model":[187],"will":[188],"be":[189],"released":[190],"at":[191],"https://github.com/DragonisCV/RAM":[192]},"counts_by_year":[],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-12T00:00:00"}