{"id":"https://openalex.org/W4313447176","doi":"https://doi.org/10.1145/3571600.3571626","title":"A Fine-Grained Vehicle Detection (FGVD) Dataset for Unconstrained Roads\u2731","display_name":"A Fine-Grained Vehicle Detection (FGVD) Dataset for Unconstrained Roads\u2731","publication_year":2022,"publication_date":"2022-12-08","ids":{"openalex":"https://openalex.org/W4313447176","doi":"https://doi.org/10.1145/3571600.3571626"},"language":"en","primary_location":{"id":"doi:10.1145/3571600.3571626","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3571600.3571626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2212.14569","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059728862","display_name":"Prafful Kumar Khoba","orcid":"https://orcid.org/0000-0002-3853-9322"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Prafful Kumar Khoba","raw_affiliation_strings":["Indian Institute of Technology Delhi, IN"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Delhi, IN","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094333252","display_name":"Chirag Parikh","orcid":"https://orcid.org/0000-0003-0216-7966"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chirag Parikh","raw_affiliation_strings":["IIIT Hyderabad, IN"],"affiliations":[{"raw_affiliation_string":"IIIT Hyderabad, IN","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053112307","display_name":"C. V. Jawahar","orcid":"https://orcid.org/0000-0001-6767-7057"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"C.V. Jawahar","raw_affiliation_strings":["IIIT Hyderabad, IN"],"affiliations":[{"raw_affiliation_string":"IIIT Hyderabad, IN","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038936106","display_name":"Ravi Kiran Sarvadevabhatla","orcid":"https://orcid.org/0000-0003-4134-1154"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ravi Kiran Sarvadevabhatla","raw_affiliation_strings":["IIIT Hyderabad, IN"],"affiliations":[{"raw_affiliation_string":"IIIT Hyderabad, IN","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061660587","display_name":"Rohit Saluja","orcid":"https://orcid.org/0000-0002-0773-3480"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rohit Saluja","raw_affiliation_strings":["IIT Mandi, IN"],"affiliations":[{"raw_affiliation_string":"IIT Mandi, IN","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5059728862"],"corresponding_institution_ids":["https://openalex.org/I68891433"],"apc_list":null,"apc_paid":null,"fwci":0.6118,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.6856708,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9984999895095825,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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-science","display_name":"Computer science","score":0.8462361097335815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6993677020072937},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6652510762214661},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5593116879463196},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5143357515335083},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4708634912967682},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4696492552757263},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4425828456878662},{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.4254192113876343},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41787150502204895},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4138604402542114}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8462361097335815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6993677020072937},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6652510762214661},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5593116879463196},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5143357515335083},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4708634912967682},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4696492552757263},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4425828456878662},{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.4254192113876343},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41787150502204895},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4138604402542114},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3571600.3571626","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3571600.3571626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2212.14569","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2212.14569","pdf_url":"https://arxiv.org/pdf/2212.14569","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:zenodo.org:7488960","is_oa":true,"landing_page_url":"https://zenodo.org/record/7488960","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/other"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2212.14569","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2212.14569","pdf_url":"https://arxiv.org/pdf/2212.14569","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5899999737739563,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1797268635","https://openalex.org/W1846799578","https://openalex.org/W1861492603","https://openalex.org/W1954152232","https://openalex.org/W1958236864","https://openalex.org/W2108598243","https://openalex.org/W2138011018","https://openalex.org/W2194775991","https://openalex.org/W2533598788","https://openalex.org/W2734501611","https://openalex.org/W2765793020","https://openalex.org/W2901870313","https://openalex.org/W2913059114","https://openalex.org/W3035172746","https://openalex.org/W3035564946","https://openalex.org/W3042011474","https://openalex.org/W3210311771","https://openalex.org/W3214154355","https://openalex.org/W4293584584","https://openalex.org/W4312696925"],"related_works":["https://openalex.org/W1517019597","https://openalex.org/W1968776045","https://openalex.org/W2296713838","https://openalex.org/W767149399","https://openalex.org/W3036261569","https://openalex.org/W2889950528","https://openalex.org/W575062473","https://openalex.org/W4297672583","https://openalex.org/W2357934771","https://openalex.org/W2971551846"],"abstract_inverted_index":{"The":[0,88,114],"previous":[1,64],"fine-grained":[2,52,186],"datasets":[3,66],"mainly":[4],"focus":[5],"on":[6,20,41,125,144],"classification":[7,65],"and":[8,86,103,111,120,159],"are":[9,178],"often":[10],"captured":[11,35],"in":[12,32,59,97,106],"a":[13,37,42,60,130,153],"controlled":[14],"setup,":[15],"with":[16,49,101,136],"the":[17,21,25,33,75,150,160,168,179,185],"camera":[18,39],"focusing":[19],"objects.":[22],"We":[23],"introduce":[24],"first":[26],"Fine-Grained":[27],"Vehicle":[28],"Detection":[29],"(FGVD)":[30],"dataset":[31,77,90,127],"wild,":[34],"from":[36],"moving":[38],"mounted":[40],"car.":[43],"It":[44],"contains":[45],"5502":[46],"scene":[47],"images":[48,177],"210":[50],"unique":[51],"labels":[53,81],"of":[54,73,132,152,155],"multiple":[55],"vehicle":[56,176],"types":[57],"organized":[58],"three-level":[61],"hierarchy.":[62],"While":[63],"also":[67,148],"include":[68],"makes":[69],"for":[70,82,140,167],"different":[71],"kinds":[72],"cars,":[74],"FGVD":[76,89,145,169,175],"introduces":[78],"new":[79],"class":[80],"categorizing":[83],"two-wheelers,":[84],"autorickshaws,":[85],"trucks.":[87],"is":[91],"challenging":[92,181],"as":[93],"it":[94],"has":[95],"vehicles":[96],"complex":[98],"traffic":[99],"scenarios":[100],"intra-class":[102],"inter-class":[104],"variations":[105],"types,":[107],"scale,":[108],"pose,":[109],"occlusion,":[110],"lighting":[112],"conditions.":[113],"current":[115],"object":[116,142],"detectors":[117,143],"like":[118],"yolov5":[119],"faster":[121],"RCNN":[122],"perform":[123],"poorly":[124],"our":[126],"due":[128],"to":[129,182],"lack":[131],"hierarchical":[133],"modeling.":[134],"Along":[135],"providing":[137],"baseline":[138],"results":[139,151],"existing":[141,157],"Dataset,":[146],"we":[147,172],"present":[149],"combination":[154],"an":[156],"detector":[158],"recent":[161],"Hierarchical":[162],"Residual":[163],"Network":[164],"(HRN)":[165],"classifier":[166],"task.":[170],"Finally,":[171],"show":[173],"that":[174],"most":[180],"classify":[183],"among":[184],"datasets.":[187],"[GitHub]":[188]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}