{"id":"https://openalex.org/W2560481731","doi":"https://doi.org/10.5220/0006097300270033","title":"Fully Convolutional Crowd Counting on Highly Congested Scenes","display_name":"Fully Convolutional Crowd Counting on Highly Congested Scenes","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2560481731","doi":"https://doi.org/10.5220/0006097300270033","mag":"2560481731"},"language":"en","primary_location":{"id":"doi:10.5220/0006097300270033","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0006097300270033","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0006097300270033","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035913336","display_name":"Mark Marsden","orcid":"https://orcid.org/0000-0002-8480-9653"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Mark Marsden","raw_affiliation_strings":["Dublin City University, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dublin City University, Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073924795","display_name":"Kevin McGuinness","orcid":"https://orcid.org/0000-0003-1336-6477"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Kevin McGuinness","raw_affiliation_strings":["Dublin City University, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dublin City University, Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022651146","display_name":"Suzanne Little","orcid":"https://orcid.org/0000-0003-3281-3471"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Suzanne Little","raw_affiliation_strings":["Dublin City University, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dublin City University, Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106498523","display_name":"Noel E. O\u2019Connor","orcid":"https://orcid.org/0000-0002-4033-9135"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Noel E. O\u2019Connor","raw_affiliation_strings":["Dublin City University, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dublin City University, Ireland","institution_ids":["https://openalex.org/I42934936"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.233,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":{"value":0.95327209,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"27","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9943000078201294,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.983299970626831,"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-science","display_name":"Computer science","score":0.7420759201049805},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6334220170974731},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6256351470947266},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6023402810096741},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5652446150779724},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4731879234313965},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.44701847434043884},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4295095205307007},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.42885932326316833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36853617429733276},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3581368625164032},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10920295119285583},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10538977384567261}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7420759201049805},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6334220170974731},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6256351470947266},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6023402810096741},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5652446150779724},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4731879234313965},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.44701847434043884},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4295095205307007},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.42885932326316833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36853617429733276},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3581368625164032},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10920295119285583},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10538977384567261},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.5220/0006097300270033","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0006097300270033","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"},{"id":"pmh:oai:doras.dcu.ie:21498","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401511","display_name":"Dublin City University Open Access Institutional Repository (Dublin City University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I42934936","host_organization_name":"Dublin City University","host_organization_lineage":["https://openalex.org/I42934936"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"pmh:oai:arXiv.org:1612.00220","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1612.00220","pdf_url":"https://arxiv.org/pdf/1612.00220","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":"","raw_type":"text"},{"id":"mag:2560481731","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1612.00220.pdf","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:http://www.rian.ie/137241/","is_oa":true,"landing_page_url":"http://doras.dcu.ie/21498/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400033","display_name":"Arrow@dit (Dublin Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I115570527","host_organization_name":"Dublin Institute of Technology","host_organization_lineage":["https://openalex.org/I115570527"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Marsden, Mark, Little, Suzanne ORCID: 0000-0003-3281-3471 &lt;https://orcid.org/0000-0003-3281-3471&gt;, McGuinness, Kevin ORCID: 0000-0003-1336-6477 &lt;https://orcid.org/0000-0003-1336-6477&gt; and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 &lt;https://orcid.org/0000-0002-4033-9135&gt;  (2017) Fully convolutional crowd counting on highly congested scenes.  In: 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), 27 Feb - 1 Mar 2017, Porto, Portugal.  ISBN 978-989-758-226-4","raw_type":"Other"},{"id":"doi:10.48550/arxiv.1612.00220","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1612.00220","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.5220/0006097300270033","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0006097300270033","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8199999928474426,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W1910776219","https://openalex.org/W1976959044","https://openalex.org/W2072232009","https://openalex.org/W2072697225","https://openalex.org/W2088929512","https://openalex.org/W2097324787","https://openalex.org/W2108598243","https://openalex.org/W2122243179","https://openalex.org/W2145983039","https://openalex.org/W2147221461","https://openalex.org/W2151666244","https://openalex.org/W2164990725","https://openalex.org/W2316109659","https://openalex.org/W2347064614","https://openalex.org/W2463631526","https://openalex.org/W2950094539","https://openalex.org/W2952932416"],"related_works":["https://openalex.org/W2463631526","https://openalex.org/W2072232009","https://openalex.org/W1910776219","https://openalex.org/W2519281173","https://openalex.org/W1976959044","https://openalex.org/W2145983039","https://openalex.org/W2123175289","https://openalex.org/W2963035940","https://openalex.org/W2520826941","https://openalex.org/W1978232622","https://openalex.org/W2541389513","https://openalex.org/W2741077351","https://openalex.org/W2514654788","https://openalex.org/W2964209782","https://openalex.org/W2207893099","https://openalex.org/W2161969291","https://openalex.org/W1686810756","https://openalex.org/W2120815373","https://openalex.org/W2075875861","https://openalex.org/W2058907003"],"abstract_inverted_index":{"In":[0],"this":[1,97],"paper":[2],"we":[3],"advance":[4],"the":[5,17,91,102,127,136,194],"state-of-the-art":[6,190],"for":[7,53,94],"crowd":[8,23,37,54],"counting":[9,24,55,76,157,191],"in":[10,49,58,82,96,101,108,117],"high":[11],"density":[12],"scenes":[13,111],"by":[14,27,126],"further":[15],"exploring":[16],"idea":[18],"of":[19,67,115,129,135,182],"a":[20,73,160,170],"fully":[21,164],"convolutional":[22,165],"model":[25,77,153],"introduced":[26],"(Zhang":[28,130],"et":[29,120,131],"al.,":[30,121,132],"2016).":[31],"Producing":[32],"an":[33],"accurate":[34],"and":[35,66,155,188,198],"robust":[36],"count":[38],"estimator":[39],"using":[40],"computer":[41],"vision":[42],"techniques":[43],"has":[44],"attracted":[45],"significant":[46],"research":[47,95],"interest":[48],"recent":[50],"years.":[51],"Applications":[52],"systems":[56],"exist":[57],"many":[59],"diverse":[60],"areas":[61],"including":[62],"city":[63],"planning,":[64],"retail,":[65],"course":[68],"general":[69],"public":[70],"safety.":[71],"Developing":[72],"highly":[74,109],"generalised":[75],"that":[78,145],"can":[79,179],"be":[80],"deployed":[81],"any":[83,87,183],"surveillance":[84],"scenario":[85],"with":[86,112],"camera":[88],"perspective":[89],"is":[90],"key":[92],"objective":[93],"area.":[98],"Techniques":[99],"developed":[100,177],"past":[103],"have":[104],"generally":[105],"performed":[106],"poorly":[107],"congested":[110],"several":[113],"thousands":[114],"people":[116],"frame":[118],"(Rodriguez":[119],"2011).":[122],"Our":[123],"approach,":[124],"influenced":[125],"work":[128],"2016),":[133],"consists":[134],"following":[137],"contributions:":[138],"(1)":[139],"A":[140],"training":[141,149],"set":[142],"augmentation":[143],"scheme":[144],"minimises":[146],"redundancy":[147],"among":[148],"samples":[150],"to":[151],"improve":[152],"generalisation":[154],"overall":[156],"performance;":[158],"(2)":[159],"deep,":[161],"single":[162],"column,":[163],"network":[166],"(FCN)":[167],"architecture;":[168],"(3)":[169],"multi-scale":[171],"averaging":[172],"step":[173],"during":[174],"inference.":[175],"The":[176],"technique":[178],"analyse":[180],"images":[181],"resolution":[184],"or":[185],"aspect":[186],"ratio":[187],"achieves":[189],"performance":[192,207],"on":[193,208],"Shanghaitech":[195,209],"Part":[196,210],"B":[197],"UCF":[199],"CC":[200],"50":[201],"datasets":[202],"as":[203,205],"well":[204],"competitive":[206],"A.":[211]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
