{"id":"https://openalex.org/W3159182652","doi":"https://doi.org/10.1145/3446918","title":"Dirty Pixels: Towards End-to-end Image Processing and Perception","display_name":"Dirty Pixels: Towards End-to-end Image Processing and Perception","publication_year":2021,"publication_date":"2021-05-05","ids":{"openalex":"https://openalex.org/W3159182652","doi":"https://doi.org/10.1145/3446918","mag":"3159182652"},"language":"en","primary_location":{"id":"doi:10.1145/3446918","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3446918","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-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/A5065985674","display_name":"Steven Diamond","orcid":"https://orcid.org/0000-0002-5523-9970"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Steven Diamond","raw_affiliation_strings":["Stanford University"],"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016061808","display_name":"Vincent Sitzmann","orcid":"https://orcid.org/0000-0002-0107-5704"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vincent Sitzmann","raw_affiliation_strings":["Stanford University, MIT"],"affiliations":[{"raw_affiliation_string":"Stanford University, MIT","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021003048","display_name":"Frank Julca-Aguilar","orcid":"https://orcid.org/0000-0001-7656-8397"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frank Julca-Aguilar","raw_affiliation_strings":["Algolux"],"affiliations":[{"raw_affiliation_string":"Algolux","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011176205","display_name":"Stephen Boyd","orcid":"https://orcid.org/0000-0001-8353-6000"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephen Boyd","raw_affiliation_strings":["Stanford University"],"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014044649","display_name":"Gordon Wetzstein","orcid":"https://orcid.org/0000-0002-9243-6885"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gordon Wetzstein","raw_affiliation_strings":["Stanford University"],"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059313827","display_name":"Felix Heide","orcid":"https://orcid.org/0000-0002-8054-9823"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Felix Heide","raw_affiliation_strings":["Princeton University"],"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5065985674"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":4.4679,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.95741447,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"40","issue":"3","first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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/T11105","display_name":"Advanced Image Processing Techniques","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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9995999932289124,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.8445718288421631},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.765982985496521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7381619215011597},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7056939601898193},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6492679119110107},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5809439420700073},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.542943000793457},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5106835961341858},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45346084237098694},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29902923107147217},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.26697608828544617}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.8445718288421631},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.765982985496521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7381619215011597},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7056939601898193},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6492679119110107},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5809439420700073},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.542943000793457},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5106835961341858},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45346084237098694},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29902923107147217},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.26697608828544617},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3446918","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3446918","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1565327149","https://openalex.org/W1912194039","https://openalex.org/W1980208272","https://openalex.org/W2006221457","https://openalex.org/W2018612061","https://openalex.org/W2021347102","https://openalex.org/W2056370875","https://openalex.org/W2083799719","https://openalex.org/W2092663520","https://openalex.org/W2097073572","https://openalex.org/W2100556411","https://openalex.org/W2122410868","https://openalex.org/W2136035751","https://openalex.org/W2142224912","https://openalex.org/W2244987555","https://openalex.org/W2331128040","https://openalex.org/W2519898457","https://openalex.org/W2526529994","https://openalex.org/W2552290192","https://openalex.org/W2556872594","https://openalex.org/W2583325387","https://openalex.org/W2593768305","https://openalex.org/W2615178951","https://openalex.org/W2620324432","https://openalex.org/W2623012778","https://openalex.org/W2735974062","https://openalex.org/W2799265886","https://openalex.org/W2807913156","https://openalex.org/W2905330967","https://openalex.org/W2952046917","https://openalex.org/W2962360676","https://openalex.org/W2962767526","https://openalex.org/W2975505153","https://openalex.org/W2982261062","https://openalex.org/W3125028070","https://openalex.org/W3143835446","https://openalex.org/W4244393449"],"related_works":["https://openalex.org/W3200192952","https://openalex.org/W2062923025","https://openalex.org/W4308216825","https://openalex.org/W4312281738","https://openalex.org/W3009226622","https://openalex.org/W3015323103","https://openalex.org/W2786875726","https://openalex.org/W4287817146","https://openalex.org/W2017449983","https://openalex.org/W2340724640"],"abstract_inverted_index":{"Real-world,":[0],"imaging":[1,34,42,214],"systems":[2],"acquire":[3],"measurements":[4,48],"that":[5,15,142,196,201,226,255],"are":[6,118,300],"degraded":[7],"by":[8,32],"noise,":[9],"optical":[10],"aberrations,":[11],"and":[12,22,61,84,115,149,167,192,215,223,235,250,283,297],"other":[13,236],"imperfections":[14],"make":[16],"image":[17,122,165,266],"processing":[18,44,169],"for":[19,92,180,242,265,281],"human":[20],"viewing":[21],"higher-level":[23,105],"perception":[24,216,231],"tasks":[25,129,285],"challenging.":[26],"Conventional":[27],"cameras":[28],"address":[29],"this":[30,87,291],"problem":[31],"compartmentalizing":[33],"from":[35,174],"high-level":[36],"task":[37,106],"processing.":[38],"As":[39],"such,":[40],"conventional":[41,213],"involves":[43,76],"the":[45,104,108,187,256,272,287],"RAW":[46],"sensor":[47],"in":[49,134,204,232,268,290],"a":[50,69,276],"sequential":[51],"pipeline":[52,64],"of":[53,103,107,176,189],"steps,":[54],"such":[55,78,130,207,245],"as":[56,79,131,208,246,275],"demosaicking,":[57,145],"denoising,":[58,146],"deblurring,":[59,147],"tone-mapping,":[60,148],"compression.":[62],"This":[63],"is":[65,202,240],"optimized":[66,179,264],"to":[67],"obtain":[68],"visually":[70],"pleasing":[71],"image.":[72],"High-level":[73],"processing,":[74],"however,":[75],"steps":[77],"feature":[80],"extraction,":[81],"classification,":[82],"tracking,":[83],"fusion.":[85],"While":[86],"silo-ed":[88],"design":[89],"approach":[90],"allows":[91],"efficient":[93],"development,":[94],"it":[95],"also":[96,259],"dictates":[97],"compartmentalized":[98],"performance":[99],"metrics":[100,124],"without":[101],"knowledge":[102],"camera":[109],"system.":[110],"For":[111],"example,":[112],"today\u2019s":[113],"demosaicking":[114],"denoising":[116],"algorithms":[117],"designed":[119],"using":[120],"perceptual":[121,181],"quality":[123,166],"but":[125],"not":[126,157],"with":[127],"domain-specific":[128],"object":[132],"detection":[133],"mind.":[135],"We":[136,194,219],"propose":[137],"an":[138],"end-to-end":[139],"differentiable":[140],"architecture":[141,155,273],"jointly":[143],"performs":[144],"classification":[150],"(see":[151],"Figure":[152],"1).":[153],"The":[154],"does":[156],"require":[158],"any":[159],"intermediate":[160],"losses":[161],"based":[162],"on":[163,221],"perceived":[164],"learns":[168],"pipelines":[170],"whose":[171],"outputs":[172],"differ":[173],"those":[175],"existing":[177],"ISPs":[178,198],"quality,":[182],"preserving":[183],"fine":[184],"detail":[185],"at":[186,302],"cost":[188],"increased":[190],"noise":[191],"artifacts.":[193],"show":[195],"state-of-the-art":[197,261],"discard":[199],"information":[200],"essential":[203],"corner":[205],"cases,":[206],"extremely":[209],"low-light":[210,269],"conditions,":[211,238,270],"where":[212],"stacks":[217],"fail.":[218],"demonstrate":[220],"captured":[222],"simulated":[224],"data":[225,299],"our":[227],"model":[228,258],"substantially":[229],"improves":[230],"low":[233],"light":[234],"challenging":[237],"which":[239],"imperative":[241],"real-world":[243],"applications":[244,288],"autonomous":[247],"driving,":[248],"robotics,":[249],"surveillance.":[251],"Finally,":[252],"we":[253],"found":[254],"proposed":[257,294],"achieves":[260],"accuracy":[262],"when":[263],"reconstruction":[267,282],"validating":[271],"itself":[274],"potentially":[277],"useful":[278],"drop-in":[279],"network":[280],"analysis":[284],"beyond":[286],"demonstrated":[289],"work.":[292],"Our":[293],"models,":[295],"datasets,":[296],"calibration":[298],"available":[301],"https://github.com/princeton-computational-imaging/DirtyPixels":[303],".":[304]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-04T08:04:53.788161","created_date":"2025-10-10T00:00:00"}
