{"id":"https://openalex.org/W3195305036","doi":"https://doi.org/10.1109/icip42928.2021.9506419","title":"Level Set Stereo For Cooperative Grouping With Occlusion","display_name":"Level Set Stereo For Cooperative Grouping With Occlusion","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3195305036","doi":"https://doi.org/10.1109/icip42928.2021.9506419","mag":"3195305036"},"language":"en","primary_location":{"id":"doi:10.1109/icip42928.2021.9506419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100677918","display_name":"Jialiang Wang","orcid":"https://orcid.org/0000-0002-2776-5703"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jialiang Wang","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073071472","display_name":"Todd Zickler","orcid":"https://orcid.org/0000-0002-3853-1558"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Todd Zickler","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2801851002"],"apc_list":null,"apc_paid":null,"fwci":0.0955,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.35122964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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":0.9980999827384949,"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":0.9959999918937683,"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/computer-vision","display_name":"Computer vision","score":0.7410850524902344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7334067225456238},{"id":"https://openalex.org/keywords/occlusion","display_name":"Occlusion","score":0.6037176251411438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6008330583572388},{"id":"https://openalex.org/keywords/jump","display_name":"Jump","score":0.5871691107749939},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5585764646530151},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5502089858055115},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5435173511505127},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32597655057907104},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25684690475463867}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7410850524902344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7334067225456238},{"id":"https://openalex.org/C2776268601","wikidata":"https://www.wikidata.org/wiki/Q968808","display_name":"Occlusion","level":2,"score":0.6037176251411438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6008330583572388},{"id":"https://openalex.org/C2780695682","wikidata":"https://www.wikidata.org/wiki/Q4005959","display_name":"Jump","level":2,"score":0.5871691107749939},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5585764646530151},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5502089858055115},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5435173511505127},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32597655057907104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25684690475463867},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip42928.2021.9506419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8399999737739563,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W845365781","https://openalex.org/W1597928342","https://openalex.org/W1604112931","https://openalex.org/W1772650917","https://openalex.org/W1910044562","https://openalex.org/W1986557010","https://openalex.org/W2030928730","https://openalex.org/W2090949637","https://openalex.org/W2107422845","https://openalex.org/W2116040950","https://openalex.org/W2117248802","https://openalex.org/W2117430149","https://openalex.org/W2121781154","https://openalex.org/W2128357735","https://openalex.org/W2133255058","https://openalex.org/W2165734775","https://openalex.org/W2173487902","https://openalex.org/W2777244778","https://openalex.org/W2950496566","https://openalex.org/W2955734197","https://openalex.org/W2963675327","https://openalex.org/W3016488419","https://openalex.org/W3211330693","https://openalex.org/W6635891682","https://openalex.org/W6676124887","https://openalex.org/W6677455522","https://openalex.org/W6776103252"],"related_works":["https://openalex.org/W2351666715","https://openalex.org/W2757332726","https://openalex.org/W1967543778","https://openalex.org/W2382902960","https://openalex.org/W3086692397","https://openalex.org/W2369384937","https://openalex.org/W2095216647","https://openalex.org/W2793265400","https://openalex.org/W2352146386","https://openalex.org/W2057933140"],"abstract_inverted_index":{"Localizing":[0],"stereo":[1,64],"boundaries":[2,28,71],"is":[3],"difficult":[4],"because":[5],"matching":[6],"cues":[7],"are":[8,15],"absent":[9],"in":[10],"the":[11,31,44,47,66],"occluded":[12],"regions":[13],"that":[14,26,50],"adjacent":[16],"to":[17],"them.":[18],"We":[19],"introduce":[20],"an":[21,40],"energy":[22],"and":[23,61],"level-set":[24],"optimizer":[25],"improves":[27],"by":[29],"encoding":[30],"essential":[32],"geometry":[33],"of":[34,39,46,56],"occlusions:":[35],"The":[36],"spatial":[37],"extent":[38],"occlusion":[41],"must":[42],"equal":[43],"amplitude":[45],"disparity":[48],"jump":[49],"causes":[51],"it.":[52],"In":[53],"a":[54],"collection":[55],"figure-ground":[57],"scenes":[58],"from":[59],"Middlebury":[60],"Falling":[62],"Things":[63],"datasets,":[65],"model":[67],"provides":[68],"more":[69],"accurate":[70],"than":[72],"previous":[73],"occlusion-handling":[74],"techniques.":[75]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}