{"id":"https://openalex.org/W4302439204","doi":"https://doi.org/10.1145/3549179.3549183","title":"Multi-Scale and Kernel-Predicting Convolutional Networks for Monte Carlo Denoising","display_name":"Multi-Scale and Kernel-Predicting Convolutional Networks for Monte Carlo Denoising","publication_year":2022,"publication_date":"2022-07-29","ids":{"openalex":"https://openalex.org/W4302439204","doi":"https://doi.org/10.1145/3549179.3549183"},"language":"en","primary_location":{"id":"doi:10.1145/3549179.3549183","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3549179.3549183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 4th International Conference on Pattern Recognition and Intelligent Systems","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/A5101904686","display_name":"Tianhan Gao","orcid":"https://orcid.org/0000-0002-0272-194X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianhan Gao","raw_affiliation_strings":["Software college, Northeastern University, China"],"affiliations":[{"raw_affiliation_string":"Software college, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034942408","display_name":"Yanjing Ge","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjing Ge","raw_affiliation_strings":["Software college, Northeastern University, China"],"affiliations":[{"raw_affiliation_string":"Software college, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101904686"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09317928,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":null,"first_page":"23","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994000196456909,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9980000257492065,"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/monte-carlo-method","display_name":"Monte Carlo method","score":0.7569182515144348},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.718714714050293},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7073372006416321},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5748523473739624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5514324307441711},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5332605242729187},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5188156962394714},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4942369759082794},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3235996663570404},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19755271077156067},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15320342779159546},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.0982958972454071}],"concepts":[{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.7569182515144348},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.718714714050293},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7073372006416321},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5748523473739624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5514324307441711},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5332605242729187},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5188156962394714},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4942369759082794},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3235996663570404},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19755271077156067},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15320342779159546},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0982958972454071},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3549179.3549183","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3549179.3549183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 4th International Conference on Pattern Recognition and Intelligent Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1971958581","https://openalex.org/W2037735934","https://openalex.org/W2090346540","https://openalex.org/W2737368828","https://openalex.org/W2738449271","https://openalex.org/W2811168853","https://openalex.org/W2903914407","https://openalex.org/W2944270038","https://openalex.org/W2958080091","https://openalex.org/W2972600666","https://openalex.org/W3014685569","https://openalex.org/W3152404362","https://openalex.org/W6631190155"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4295815739","https://openalex.org/W2915512385"],"abstract_inverted_index":{"Monte":[0,19,81],"Carlo":[1,20,82],"rendering":[2,17,21,30],"has":[3],"been":[4],"widely":[5],"used":[6],"in":[7,77],"many":[8],"fields,":[9],"such":[10],"as":[11],"movies,":[12],"which":[13,124],"pursue":[14],"the":[15,33,47,50,58,78,132],"photorealistic":[16],"effect.":[18],"needs":[22],"high":[23],"sampling":[24,55],"rates":[25],"to":[26,45,74],"get":[27],"an":[28],"accurate":[29],"effect,":[31],"but":[32],"calculation":[34],"cost":[35],"is":[36,44,62,72],"expensive.":[37],"To":[38],"keep":[39],"costs":[40],"down,":[41],"one":[42],"solution":[43],"reduce":[46],"noise":[48,76,129],"of":[49],"rendered":[51],"image":[52],"at":[53,121],"reduced":[54],"rates.":[56],"Because":[57],"traditional":[59],"denoising":[60,83,92,133],"method":[61,84,113],"based":[63,85],"on":[64,86],"higher":[65,67],"and":[66,117,130],"order":[68],"regression":[69],"models,":[70],"it":[71],"prone":[73],"overfitting":[75],"input.":[79],"The":[80],"deep":[87],"learning":[88,120],"shows":[89],"a":[90,99,104],"certain":[91],"value.":[93],"In":[94],"this":[95],"paper,":[96],"we":[97],"propose":[98],"kernel-predicting":[100],"convolutional":[101],"network":[102],"with":[103,109],"multi-scale":[105],"residual":[106,119],"structure.":[107],"Compared":[108],"previous":[110],"methods,":[111],"our":[112],"can":[114,125],"extract":[115],"features":[116],"perform":[118],"different":[122],"scales,":[123],"further":[126],"remove":[127],"low-frequency":[128],"improve":[131],"quality.":[134]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}