{"id":"https://openalex.org/W4205458661","doi":"https://doi.org/10.1109/vcip53242.2021.9675373","title":"SalGFCN: Graph Based Fully Convolutional Network for Panoramic Saliency Prediction","display_name":"SalGFCN: Graph Based Fully Convolutional Network for Panoramic Saliency Prediction","publication_year":2021,"publication_date":"2021-12-05","ids":{"openalex":"https://openalex.org/W4205458661","doi":"https://doi.org/10.1109/vcip53242.2021.9675373"},"language":"en","primary_location":{"id":"doi:10.1109/vcip53242.2021.9675373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip53242.2021.9675373","pdf_url":null,"source":{"id":"https://openalex.org/S4363608378","display_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","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/A5101822450","display_name":"Yiwei Yang","orcid":"https://orcid.org/0000-0001-8531-0574"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiwei Yang","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034718093","display_name":"Yucheng Zhu","orcid":"https://orcid.org/0000-0002-3069-060X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yucheng Zhu","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047926878","display_name":"Zhongpai Gao","orcid":"https://orcid.org/0000-0003-4344-4501"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongpai Gao","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064168853","display_name":"Guangtao Zhai","orcid":"https://orcid.org/0000-0001-8165-9322"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangtao Zhai","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101822450"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.2614,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.65236175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9905999898910522,"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":0.9785000085830688,"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/computer-science","display_name":"Computer science","score":0.7178260087966919},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.7032997608184814},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6981642246246338},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6213760375976562},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5577627420425415},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5207545757293701},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4920575022697449},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43897661566734314},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.29298296570777893},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2312951385974884}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7178260087966919},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.7032997608184814},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6981642246246338},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6213760375976562},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5577627420425415},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5207545757293701},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4920575022697449},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43897661566734314},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29298296570777893},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2312951385974884}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip53242.2021.9675373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip53242.2021.9675373","pdf_url":null,"source":{"id":"https://openalex.org/S4363608378","display_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G362067798","display_name":null,"funder_award_id":"62101326,61901260,61831015,U1908210,61927809,61771305","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2046346382","https://openalex.org/W2088252378","https://openalex.org/W2212216676","https://openalex.org/W2738767782","https://openalex.org/W2774320778","https://openalex.org/W2793668851","https://openalex.org/W2794956947","https://openalex.org/W2803485280","https://openalex.org/W2895640967","https://openalex.org/W2902009049","https://openalex.org/W2908510526","https://openalex.org/W2963121255","https://openalex.org/W2963503775","https://openalex.org/W2964015378","https://openalex.org/W2969261403","https://openalex.org/W3000351820","https://openalex.org/W3033818674","https://openalex.org/W3035649237","https://openalex.org/W3092992156","https://openalex.org/W3125786462","https://openalex.org/W3187966659","https://openalex.org/W4288419263","https://openalex.org/W6726873649","https://openalex.org/W6739778489","https://openalex.org/W6757817989","https://openalex.org/W6760045743","https://openalex.org/W6763349780","https://openalex.org/W6769516661","https://openalex.org/W6780017182","https://openalex.org/W6783243524"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W2810679507","https://openalex.org/W4300237897","https://openalex.org/W2084942241","https://openalex.org/W3015684221"],"abstract_inverted_index":{"The":[0,61],"saliency":[1,20,43,62,112],"prediction":[2,44,63],"of":[3,45],"panoramic":[4,52],"images":[5,25],"is":[6,65],"dramatically":[7],"affected":[8],"by":[9,13],"the":[10,79,115],"distortion":[11],"caused":[12],"non-Euclidean":[14],"geometry":[15],"characteristic.":[16],"Traditional":[17],"CNN":[18],"based":[19,38,66],"pre-diction":[21],"algorithms":[22],"for":[23,30,42,59,88],"2D":[24],"are":[26],"no":[27],"longer":[28],"suitable":[29],"360-degree":[31,46],"images.":[32],"Intuitively,":[33],"we":[34,82],"propose":[35],"a":[36,84],"graph":[37,56,73,89,96],"fully":[39,85],"convolutional":[40,86],"network":[41,64],"images,":[47],"which":[48],"can":[49],"reasonably":[50],"map":[51],"pixels":[53],"to":[54,98],"spherical":[55,95],"data":[57],"structures":[58],"representation.":[60],"on":[67,114],"residual":[68],"U-Net":[69],"architecture,":[70],"with":[71],"dilated":[72],"convolutions":[74],"and":[75,91],"attention":[76],"mechanism":[77],"in":[78,94],"bottleneck.":[80],"Furthermore,":[81],"design":[83],"layer":[87],"pooling":[90],"unpooling":[92],"operations":[93],"space":[97],"retain":[99],"node-to-node":[100],"features.":[101],"Experimental":[102],"results":[103],"show":[104],"that":[105],"our":[106],"proposed":[107],"method":[108],"outperforms":[109],"other":[110],"state-of-the-art":[111],"models":[113],"large-scale":[116],"dataset.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}