{"id":"https://openalex.org/W2913368113","doi":"https://doi.org/10.1109/avss.2018.8639110","title":"Improving Real-Time Pedestrian Detectors with RGB+Depth Fusion","display_name":"Improving Real-Time Pedestrian Detectors with RGB+Depth Fusion","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2913368113","doi":"https://doi.org/10.1109/avss.2018.8639110","mag":"2913368113"},"language":"en","primary_location":{"id":"doi:10.1109/avss.2018.8639110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2018.8639110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://lirias.kuleuven.be/handle/123456789/629941","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080935182","display_name":"Tanguy Ophoff","orcid":"https://orcid.org/0000-0001-8679-6828"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Tanguy Ophoff","raw_affiliation_strings":["EAVISE - Campus De Nayer, KU Leuven, Sint-Katelijne-Waver, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EAVISE - Campus De Nayer, KU Leuven, Sint-Katelijne-Waver, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085816625","display_name":"Kristof Van Beeck","orcid":"https://orcid.org/0000-0002-3667-7406"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Kristof Van Beeck","raw_affiliation_strings":["EAVISE - Campus De Nayer, KU Leuven, Sint-Katelijne-Waver, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EAVISE - Campus De Nayer, KU Leuven, Sint-Katelijne-Waver, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057957125","display_name":"Toon Goedem\u00e9","orcid":"https://orcid.org/0000-0002-7477-8961"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Toon Goedeme","raw_affiliation_strings":["EAVISE - Campus De Nayer, KU Leuven, Sint-Katelijne-Waver, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EAVISE - Campus De Nayer, KU Leuven, Sint-Katelijne-Waver, Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99464096"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9991000294685364,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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":0.8095967769622803},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.7770174145698547},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.7512710094451904},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6818275451660156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6780014038085938},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6219513416290283},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.604946494102478},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5492191910743713},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.44820597767829895},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.3853362500667572},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07450199127197266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8095967769622803},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.7770174145698547},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.7512710094451904},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6818275451660156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6780014038085938},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6219513416290283},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.604946494102478},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5492191910743713},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.44820597767829895},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.3853362500667572},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07450199127197266},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/avss.2018.8639110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2018.8639110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/629941","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/629941","pdf_url":null,"source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS) - MSS Workshop, Auckland, New Zealand, 27-30 November 2018","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/629941","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/629941","pdf_url":null,"source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS) - MSS Workshop, Auckland, New Zealand, 27-30 November 2018","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1677182931","https://openalex.org/W1861492603","https://openalex.org/W1893035343","https://openalex.org/W1910108985","https://openalex.org/W2099570340","https://openalex.org/W2102605133","https://openalex.org/W2120419212","https://openalex.org/W2125556102","https://openalex.org/W2130306094","https://openalex.org/W2136724559","https://openalex.org/W2150066425","https://openalex.org/W2159386181","https://openalex.org/W2163605009","https://openalex.org/W2168195382","https://openalex.org/W2194775991","https://openalex.org/W2511791013","https://openalex.org/W2570343428","https://openalex.org/W2576587566","https://openalex.org/W2591954754","https://openalex.org/W2613718673","https://openalex.org/W2741620214","https://openalex.org/W2807577763","https://openalex.org/W2902314041","https://openalex.org/W2963037989","https://openalex.org/W2963188557","https://openalex.org/W3106250896","https://openalex.org/W6620707391","https://openalex.org/W6639102338","https://openalex.org/W6639812447","https://openalex.org/W6679349572","https://openalex.org/W6684191040","https://openalex.org/W6725558437","https://openalex.org/W6730018194","https://openalex.org/W6756834165","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2031175860","https://openalex.org/W2152662039","https://openalex.org/W2726747157","https://openalex.org/W2004817612"],"abstract_inverted_index":{"In":[0],"this":[1,43],"paper":[2],"we":[3,93],"investigate":[4,37],"the":[5,38,82],"benefit":[6],"of":[7,13,72,116],"using":[8,26],"depth":[9,21,27,68],"information":[10],"on":[11,50,58,135],"top":[12],"normal":[14],"RGB":[15,87],"for":[16],"camera-based":[17],"pedestrian":[18],"detection.":[19],"Indeed,":[20],"sensing":[22],"is":[23,99,119,128],"easily":[24],"acquired":[25],"cameras":[28],"such":[29],"as":[30],"a":[31,47,85,105,113],"Kinect":[32],"or":[33],"stereo":[34],"setups.":[35],"We":[36,61],"best":[39],"way":[40],"to":[41],"perform":[42],"sensor":[44],"fusion":[45,80,97],"with":[46],"special":[48],"focus":[49],"lightweight":[51],"single-pass":[52],"CNN":[53],"architectures,":[54,65],"enabling":[55],"real-time":[56,133],"processing":[57],"limited":[59],"hardware.":[60],"implement":[62],"different":[63,70],"network":[64,98,127],"each":[66],"fusing":[67],"at":[69,101,121],"layers":[71],"our":[73,96],"network.":[74],"Our":[75],"experiments":[76],"show":[77],"that":[78,95,109],"midway":[79],"performs":[81],"best,":[83],"outperforming":[84],"regular":[86],"detector":[88],"substantially":[89],"in":[90,104],"accuracy.":[91],"Moreover,":[92],"prove":[94],"better":[100,114,120],"detecting":[102],"individuals":[103],"crowd,":[106],"by":[107],"demonstrating":[108],"it":[110],"has":[111],"both":[112,136],"localization":[115],"pedestrians":[117],"and":[118,131,138],"handling":[122],"occluded":[123],"persons.":[124],"The":[125],"resulting":[126],"computationally":[129],"efficient":[130],"achieves":[132],"performance":[134],"desktop":[137],"embedded":[139],"GPUs.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
