{"id":"https://openalex.org/W4200073446","doi":"https://doi.org/10.1108/ir-06-2021-0118","title":"Real-time pixel-wise grasp affordance prediction based on multi-scale context information fusion","display_name":"Real-time pixel-wise grasp affordance prediction based on multi-scale context information fusion","publication_year":2021,"publication_date":"2021-12-28","ids":{"openalex":"https://openalex.org/W4200073446","doi":"https://doi.org/10.1108/ir-06-2021-0118"},"language":"en","primary_location":{"id":"doi:10.1108/ir-06-2021-0118","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ir-06-2021-0118","pdf_url":null,"source":{"id":"https://openalex.org/S166948985","display_name":"Industrial Robot the international journal of robotics research and application","issn_l":"0143-991X","issn":["0143-991X","1758-5791"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Industrial Robot: the international journal of robotics research and application","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/A5037570916","display_name":"Yongxiang Wu","orcid":"https://orcid.org/0000-0002-1374-9788"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongxiang Wu","raw_affiliation_strings":["State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008597054","display_name":"Yili Fu","orcid":"https://orcid.org/0000-0003-2075-2384"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yili Fu","raw_affiliation_strings":["State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102733721","display_name":"Shuguo Wang","orcid":"https://orcid.org/0009-0005-1772-3701"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuguo Wang","raw_affiliation_strings":["State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037570916"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.6867,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70431835,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"49","issue":"2","first_page":"368","last_page":"381"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/grasp","display_name":"GRASP","score":0.7102174758911133},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7097098231315613},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7094325423240662},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5990889072418213},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5937118530273438},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5373415350914001},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5336081981658936},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5162520408630371},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4943053722381592},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4897189438343048},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4399515390396118},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4314318895339966},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.42155763506889343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37304753065109253},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3612115979194641},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36019009351730347},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12702301144599915},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10379624366760254}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.7102174758911133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7097098231315613},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7094325423240662},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5990889072418213},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5937118530273438},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5373415350914001},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5336081981658936},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5162520408630371},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4943053722381592},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4897189438343048},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4399515390396118},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4314318895339966},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.42155763506889343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37304753065109253},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3612115979194641},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36019009351730347},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12702301144599915},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10379624366760254},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/ir-06-2021-0118","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ir-06-2021-0118","pdf_url":null,"source":{"id":"https://openalex.org/S166948985","display_name":"Industrial Robot the international journal of robotics research and application","issn_l":"0143-991X","issn":["0143-991X","1758-5791"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Industrial Robot: the international journal of robotics research and application","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1892339738","https://openalex.org/W1899185266","https://openalex.org/W1999156278","https://openalex.org/W2123435073","https://openalex.org/W2194775991","https://openalex.org/W2201912979","https://openalex.org/W2557924869","https://openalex.org/W2572996265","https://openalex.org/W2600030077","https://openalex.org/W2618530766","https://openalex.org/W2736762515","https://openalex.org/W2761290119","https://openalex.org/W2792716148","https://openalex.org/W2794784791","https://openalex.org/W2798255267","https://openalex.org/W2805051407","https://openalex.org/W2808521881","https://openalex.org/W2824754393","https://openalex.org/W2913267332","https://openalex.org/W2953669419","https://openalex.org/W2963550225","https://openalex.org/W2967869116","https://openalex.org/W2972384215","https://openalex.org/W3003650992","https://openalex.org/W3034399919"],"related_works":["https://openalex.org/W2557924869","https://openalex.org/W2389377526","https://openalex.org/W3002446410","https://openalex.org/W2889260105","https://openalex.org/W2890646997","https://openalex.org/W2337415362","https://openalex.org/W4319018800","https://openalex.org/W4312857205","https://openalex.org/W121273120","https://openalex.org/W2756241593"],"abstract_inverted_index":{"Purpose":[0],"This":[1],"paper":[2],"aims":[3],"to":[4,10,39,62,80,108,170,217],"use":[5],"fully":[6],"convolutional":[7],"network":[8,33,104,164,209],"(FCN)":[9],"predict":[11,109],"pixel-wise":[12,41,205],"antipodal":[13],"grasp":[14,22,83,111,206,220],"affordances":[15],"for":[16,113,183,187,192],"unknown":[17,123,198],"objects":[18,189,193],"and":[19,88,90,95,118,172,178,190,228,246],"improve":[20,218],"the":[21,37,44,69,110,130,136,142,149,197,219,232],"detection":[23,221],"performance":[24],"through":[25],"multi-scale":[26,52,137,212],"feature":[27,72,155,213],"fusion.":[28],"Design/methodology/approach":[29],"A":[30,203],"modified":[31],"FCN":[32],"is":[34,105,215],"used":[35],"as":[36],"backbone":[38],"extract":[40],"features":[42],"from":[43],"input":[45],"image,":[46],"which":[47],"are":[48,78,93,226],"further":[49,106],"fused":[50],"with":[51,97,115],"context":[53],"information":[54,138],"gathered":[55],"by":[56],"a":[57,98,166],"three-level":[58],"pyramid":[59,131],"pooling":[60,132],"module":[61,133],"make":[63],"more":[64],"robust":[65],"predictions.":[66],"Based":[67],"on":[68,153,158,211,231,241],"proposed":[70,216,233,236],"unify":[71],"embedding":[73,156],"framework,":[74],"two":[75,159],"head":[76],"networks":[77],"designed":[79],"implement":[81],"different":[82],"rotation":[84],"prediction":[85,208,224],"strategies":[86],"(regression":[87],"classification),":[89],"their":[91],"performances":[92,240],"evaluated":[94],"compared":[96,229],"defined":[99],"point":[100],"metric.":[101],"The":[102,126,145,162,235],"regression":[103,146,163],"extended":[107],"rectangles":[112],"comparisons":[114],"previous":[116],"methods":[117],"real-world":[119,247],"robotic":[120,248],"grasping":[121,200,249],"of":[122,129],"objects.":[124],"Findings":[125],"ablation":[127],"study":[128],"shows":[134],"that":[135],"fusion":[139,214],"significantly":[140],"improves":[141],"model":[143],"performance.":[144,222],"approach":[147,151],"outperforms":[148],"classification":[150],"based":[152,210,230],"same":[154],"framework":[157],"data":[160,244],"sets.":[161],"achieves":[165,238],"state-of-the-art":[167],"accuracy":[168],"(up":[169],"98.9%)":[171],"speed":[173],"(4":[174],"ms":[175],"per":[176],"image)":[177],"high":[179],"success":[180],"rate":[181],"(97%":[182],"household":[184],"objects,":[185],"94.4%":[186],"adversarial":[188],"95.3%":[191],"in":[194,196],"clutter)":[195],"object":[199],"experiment.":[201,250],"Originality/value":[202],"novel":[204],"affordance":[207],"Two":[223],"approaches":[225],"formulated":[227],"framework.":[234],"method":[237],"excellent":[239],"three":[242],"benchmark":[243],"sets":[245]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}