{"id":"https://openalex.org/W7160431900","doi":"https://doi.org/10.48550/arxiv.2605.03626","title":"RPBA-Net: An Interpretable Residual Pyramid Bilateral Affine Network for RAW-Domain ISP Enhancement","display_name":"RPBA-Net: An Interpretable Residual Pyramid Bilateral Affine Network for RAW-Domain ISP Enhancement","publication_year":2026,"publication_date":"2026-05-05","ids":{"openalex":"https://openalex.org/W7160431900","doi":"https://doi.org/10.48550/arxiv.2605.03626"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.03626","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03626","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.03626","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135525012","display_name":"Yucheng Xin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin, Yucheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135467877","display_name":"Wu Chen","orcid":"https://orcid.org/0000-0002-5923-5758"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135484471","display_name":"Xiang Chen","orcid":"https://orcid.org/0000-0002-7176-2753"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135437916","display_name":"Guangwei Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Guangwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135468478","display_name":"Xinchun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xinchun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125508867","display_name":"Ruize Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Ruize","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135522815","display_name":"Dianjie Lu","orcid":"https://orcid.org/0000-0001-5435-5307"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Dianjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135505898","display_name":"Guijuan Zhang","orcid":"https://orcid.org/0009-0009-1555-8385"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Guijuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135505525","display_name":"Linwei Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Linwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135535173","display_name":"Zhuoran Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Zhuoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T11019","display_name":"Image Enhancement Techniques","score":0.9828000068664551,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9828000068664551,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.006200000178068876,"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":0.0017000000225380063,"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/affine-transformation","display_name":"Affine transformation","score":0.7839000225067139},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6845999956130981},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5450999736785889},{"id":"https://openalex.org/keywords/affine-shape-adaptation","display_name":"Affine shape adaptation","score":0.4918000102043152},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.45680001378059387},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4284000098705292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4065999984741211},{"id":"https://openalex.org/keywords/tone-mapping","display_name":"Tone mapping","score":0.3783999979496002},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.3617999851703644}],"concepts":[{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.7839000225067139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7039999961853027},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6845999956130981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5874999761581421},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5450999736785889},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5202000141143799},{"id":"https://openalex.org/C18516315","wikidata":"https://www.wikidata.org/wiki/Q4688950","display_name":"Affine shape adaptation","level":4,"score":0.4918000102043152},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.45680001378059387},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4284000098705292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40119999647140503},{"id":"https://openalex.org/C8641274","wikidata":"https://www.wikidata.org/wiki/Q1030958","display_name":"Tone mapping","level":4,"score":0.3783999979496002},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C207221997","wikidata":"https://www.wikidata.org/wiki/Q938614","display_name":"Affine combination","level":3,"score":0.34779998660087585},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3310999870300293},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3239000141620636},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.3003000020980835},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.29600000381469727},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29010000824928284},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2603999972343445},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.03626","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03626","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.03626","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03626","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4021259546279907,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"To":[0],"address":[1],"module":[2],"fragmentation,":[3],"uninterpretable":[4],"mappings,":[5],"and":[6,14,50,59,68,84,93,104,116,123,131,137],"deployment":[7,133],"constraints":[8],"in":[9,120],"RAW-domain":[10,29],"demosaicing,":[11],"color":[12],"correction,":[13],"detail":[15],"enhancement,":[16],"this":[17],"paper":[18],"proposes":[19],"RPBA-Net,":[20],"an":[21],"interpretable":[22],"residual":[23,40,53],"pyramid":[24,64],"bilateral":[25,65],"affine":[26,41,54,66],"network":[27],"for":[28,135],"ISP":[30],"enhancement.":[31,60,87],"Given":[32],"packed":[33],"RAW":[34],"as":[35],"input,":[36],"the":[37],"method":[38],"performs":[39],"base":[42,47],"reconstruction":[43,121],"by":[44],"estimating":[45],"a":[46],"RGB":[48],"representation":[49],"learning":[51],"identity-guided":[52],"corrections,":[55],"thereby":[56],"unifying":[57],"demosaicing":[58],"It":[61],"further":[62],"builds":[63],"grids":[67],"combines":[69],"guide-driven":[70],"autoregressive":[71],"adaptive":[72,75],"slicing":[73],"with":[74],"cross-layer":[76],"fusion":[77],"to":[78,99],"hierarchically":[79],"model":[80,101,129],"global":[81],"tone":[82],"restoration":[83],"local":[85],"texture":[86],"In":[88],"addition,":[89],"smoothness,":[90],"cross-scale":[91],"consistency,":[92],"magnitude":[94],"regularization":[95],"terms":[96],"are":[97],"introduced":[98],"improve":[100],"stability,":[102],"controllability,":[103],"structural":[105],"interpretability.":[106],"Extensive":[107],"experiments":[108],"demonstrate":[109],"that":[110],"RPBA-Net":[111],"surpasses":[112],"representative":[113],"RAW-to-sRGB":[114],"methods":[115],"achieves":[117],"state-of-the-art":[118],"performance":[119],"fidelity":[122],"perceptual":[124],"quality,":[125],"while":[126],"maintaining":[127],"low":[128],"complexity":[130],"strong":[132],"potential":[134],"mobile":[136],"embedded":[138],"platforms.":[139]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-07T00:00:00"}
