{"id":"https://openalex.org/W4392248370","doi":"https://doi.org/10.1109/icce59016.2024.10444165","title":"Spatio-Temporal Consistent Non-homogeneous Extreme Video Retargeting","display_name":"Spatio-Temporal Consistent Non-homogeneous Extreme Video Retargeting","publication_year":2024,"publication_date":"2024-01-06","ids":{"openalex":"https://openalex.org/W4392248370","doi":"https://doi.org/10.1109/icce59016.2024.10444165"},"language":"en","primary_location":{"id":"doi:10.1109/icce59016.2024.10444165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce59016.2024.10444165","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","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/A5023872482","display_name":"Hassan Imani","orcid":"https://orcid.org/0000-0003-1566-3897"},"institutions":[{"id":"https://openalex.org/I128277893","display_name":"Bah\u00e7e\u015fehir University","ror":"https://ror.org/00yze4d93","country_code":"TR","type":"education","lineage":["https://openalex.org/I128277893"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Hassan Imani","raw_affiliation_strings":["Bahcesehir University,Department of Computer Engineering,Istanbul,Turky","Department of Computer Engineering, Bahcesehir University, Istanbul, Turky"],"affiliations":[{"raw_affiliation_string":"Bahcesehir University,Department of Computer Engineering,Istanbul,Turky","institution_ids":["https://openalex.org/I128277893"]},{"raw_affiliation_string":"Department of Computer Engineering, Bahcesehir University, Istanbul, Turky","institution_ids":["https://openalex.org/I128277893"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033078932","display_name":"Md Baharul Islam","orcid":"https://orcid.org/0000-0002-9928-5776"},"institutions":[{"id":"https://openalex.org/I128277893","display_name":"Bah\u00e7e\u015fehir University","ror":"https://ror.org/00yze4d93","country_code":"TR","type":"education","lineage":["https://openalex.org/I128277893"]},{"id":"https://openalex.org/I2801014300","display_name":"Florida Gulf Coast University","ror":"https://ror.org/05tc5bm31","country_code":"US","type":"education","lineage":["https://openalex.org/I2801014300"]}],"countries":["TR","US"],"is_corresponding":false,"raw_author_name":"Md Baharul Islam","raw_affiliation_strings":["Florida Gulf Coast University, United States Bahcesehir University,Istanbul,Turkey","Florida Gulf Coast University, United States Bahcesehir University, Istanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Florida Gulf Coast University, United States Bahcesehir University,Istanbul,Turkey","institution_ids":["https://openalex.org/I128277893","https://openalex.org/I2801014300"]},{"raw_affiliation_string":"Florida Gulf Coast University, United States Bahcesehir University, Istanbul, Turkey","institution_ids":["https://openalex.org/I128277893","https://openalex.org/I2801014300"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023872482"],"corresponding_institution_ids":["https://openalex.org/I128277893"],"apc_list":null,"apc_paid":null,"fwci":0.5263,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61139483,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9994000196456909,"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/T11605","display_name":"Visual Attention and Saliency Detection","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"}}],"keywords":[{"id":"https://openalex.org/keywords/retargeting","display_name":"Retargeting","score":0.9073465466499329},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.7035611867904663},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6609979271888733},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.46479174494743347},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4140647351741791},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36548876762390137},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09974244236946106}],"concepts":[{"id":"https://openalex.org/C2780575108","wikidata":"https://www.wikidata.org/wiki/Q7316652","display_name":"Retargeting","level":2,"score":0.9073465466499329},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.7035611867904663},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6609979271888733},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.46479174494743347},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4140647351741791},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36548876762390137},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09974244236946106},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce59016.2024.10444165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce59016.2024.10444165","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2018377917","https://openalex.org/W2115273023","https://openalex.org/W2470139095","https://openalex.org/W2528578439","https://openalex.org/W2565639579","https://openalex.org/W2604329646","https://openalex.org/W2922109113","https://openalex.org/W2963083275","https://openalex.org/W2963334022","https://openalex.org/W2964251418","https://openalex.org/W2997421813","https://openalex.org/W3009014607","https://openalex.org/W3011906828","https://openalex.org/W3037236009","https://openalex.org/W3039991645","https://openalex.org/W3118401715","https://openalex.org/W3195305640","https://openalex.org/W4220704433","https://openalex.org/W4226091384","https://openalex.org/W4362654014","https://openalex.org/W6637373629","https://openalex.org/W6760643166","https://openalex.org/W6780122746"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Due":[0],"to":[1,60,71,98,123,136,141,147,159],"the":[2,65,72,78,99,105,113,129,133,143,148,166,178,182,185,189],"availability":[3],"of":[4,184],"heterogeneous":[5],"display":[6],"devices":[7],"and":[8,30,68,89,95,102,155,171,174],"their":[9],"aspect":[10],"ratios,":[11],"video":[12,22,45],"retargeting":[13,23,36],"has":[14],"received":[15],"considerable":[16],"research":[17],"attention":[18],"among":[19],"researchers.":[20],"Non-consistent":[21],"can":[24],"significantly":[25],"affect":[26],"a":[27,56,82,90,119,137],"video\u2019s":[28],"spatial":[29],"temporal":[31,125],"quality,":[32],"particularly":[33],"for":[34,44,111],"extreme":[35],"cases.":[37],"Since":[38],"no":[39],"perfectly":[40],"annotated":[41],"datasets":[42],"exist":[43],"retargeting,":[46],"deep":[47],"learning-based":[48],"techniques":[49],"are":[50],"rarely":[51],"utilized.":[52],"This":[53],"paper":[54],"proposes":[55],"method":[57,187],"that":[58],"learns":[59],"retarget":[61],"videos":[62],"by":[63],"detecting":[64],"salient":[66,79,114],"areas":[67],"shifting":[69,91,112],"them":[70],"appropriate":[73],"location.":[74],"First,":[75],"we":[76,93,131,152,164],"segment":[77],"objects":[80,97],"using":[81],"unified":[83],"Transformer":[84],"model.":[85,162],"Using":[86],"convolutional":[87],"layers":[88],"strategy,":[92],"shift":[94],"warp":[96],"suitable":[100],"size":[101],"location":[103],"in":[104],"frame.":[106],"We":[107,116],"use":[108,118],"1D":[109],"convolution":[110],"objects.":[115],"also":[117],"frame":[120],"interpolation":[121],"technique":[122],"preserve":[124],"information.":[126],"To":[127],"train":[128,160,165],"network,":[130],"feed":[132],"retargeted":[134,144],"frames":[135,145],"variational":[138],"auto-encoder":[139],"network":[140,167],"map":[142],"back":[146],"input":[149],"frames.":[150],"Besides,":[151],"design":[153],"perceptual":[154],"wavelet-based":[156],"loss":[157],"functions":[158],"our":[161],"Thus,":[163],"unsupervised.":[168],"Extensive":[169],"qualitative":[170],"quantitative":[172],"experiments":[173],"ablation":[175],"studies":[176],"on":[177],"DAVIS":[179],"dataset":[180],"show":[181],"superiority":[183],"proposed":[186],"over":[188],"existing":[190],"state-of-the-art":[191],"methods.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
