{"id":"https://openalex.org/W3017213894","doi":"https://doi.org/10.1109/cvpr42600.2020.00009","title":"Footprints and Free Space From a Single Color Image","display_name":"Footprints and Free Space From a Single Color Image","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3017213894","doi":"https://doi.org/10.1109/cvpr42600.2020.00009","mag":"3017213894"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr42600.2020.00009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr42600.2020.00009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2004.06376","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103460915","display_name":"J.S. Watson","orcid":"https://orcid.org/0000-0001-7461-5663"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jamie Watson","raw_affiliation_strings":["Niantic"],"affiliations":[{"raw_affiliation_string":"Niantic","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028022598","display_name":"Michael Firman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Firman","raw_affiliation_strings":["Niantic"],"affiliations":[{"raw_affiliation_string":"Niantic","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016840801","display_name":"\u00c1ron Monszpart","orcid":"https://orcid.org/0000-0003-0579-5300"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aron Monszpart","raw_affiliation_strings":["Niantic"],"affiliations":[{"raw_affiliation_string":"Niantic","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038405331","display_name":"Gabriel Brostow","orcid":"https://orcid.org/0000-0001-8472-3828"},"institutions":[{"id":"https://openalex.org/I2801187875","display_name":"University College Lahore","ror":"https://ror.org/0572v5y16","country_code":"PK","type":"education","lineage":["https://openalex.org/I2801187875"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Gabriel J. Brostow","raw_affiliation_strings":["Niantic","UCL"],"affiliations":[{"raw_affiliation_string":"Niantic","institution_ids":[]},{"raw_affiliation_string":"UCL","institution_ids":["https://openalex.org/I2801187875"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103460915"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0982,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.37438891,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"11","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10531","display_name":"Advanced Vision and Imaging","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10812","display_name":"Human Pose and Action Recognition","score":0.9972000122070312,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.782374382019043},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.739027738571167},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7165228128433228},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5612115263938904},{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.4840675890445709},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46491605043411255},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.456514835357666},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4360868036746979},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.4336312711238861},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4240376651287079},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4136950373649597},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.34361934661865234}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.782374382019043},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.739027738571167},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7165228128433228},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5612115263938904},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.4840675890445709},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46491605043411255},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.456514835357666},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4360868036746979},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4336312711238861},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4240376651287079},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4136950373649597},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.34361934661865234},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/cvpr42600.2020.00009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr42600.2020.00009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2004.06376","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.06376","pdf_url":"https://arxiv.org/pdf/2004.06376","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:3017213894","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2004.06376","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:oai:eprints.ucl.ac.uk.OAI2:10117261","is_oa":false,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10117261/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In:  Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).  (pp. pp. 11-20).  The Institute of Electrical and Electronics Engineers (IEEE) (2020)     ","raw_type":"Proceedings paper"},{"id":"doi:10.48550/arxiv.2004.06376","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2004.06376","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":"pmh:oai:arXiv.org:2004.06376","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.06376","pdf_url":"https://arxiv.org/pdf/2004.06376","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"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3017213894.pdf","grobid_xml":"https://content.openalex.org/works/W3017213894.grobid-xml"},"referenced_works_count":104,"referenced_works":["https://openalex.org/W244217497","https://openalex.org/W331766535","https://openalex.org/W796515066","https://openalex.org/W1966931935","https://openalex.org/W1969483458","https://openalex.org/W1987266124","https://openalex.org/W1987648924","https://openalex.org/W1991717955","https://openalex.org/W2004887586","https://openalex.org/W2005175937","https://openalex.org/W2018299767","https://openalex.org/W2030358157","https://openalex.org/W2032293070","https://openalex.org/W2044233231","https://openalex.org/W2061482346","https://openalex.org/W2085261163","https://openalex.org/W2099144379","https://openalex.org/W2112070512","https://openalex.org/W2113107168","https://openalex.org/W2143220699","https://openalex.org/W2145567954","https://openalex.org/W2150066425","https://openalex.org/W2152571752","https://openalex.org/W2171740948","https://openalex.org/W2229637417","https://openalex.org/W2336968928","https://openalex.org/W2340897893","https://openalex.org/W2342277278","https://openalex.org/W2444097022","https://openalex.org/W2460280001","https://openalex.org/W2464328412","https://openalex.org/W2520707372","https://openalex.org/W2523049145","https://openalex.org/W2534523274","https://openalex.org/W2535547924","https://openalex.org/W2557465155","https://openalex.org/W2560544142","https://openalex.org/W2561196672","https://openalex.org/W2593841437","https://openalex.org/W2598108580","https://openalex.org/W2609883120","https://openalex.org/W2737258237","https://openalex.org/W2755286543","https://openalex.org/W2784516840","https://openalex.org/W2788897767","https://openalex.org/W2794627954","https://openalex.org/W2794752562","https://openalex.org/W2798410215","https://openalex.org/W2798976292","https://openalex.org/W2883907768","https://openalex.org/W2884654623","https://openalex.org/W2887848798","https://openalex.org/W2890949887","https://openalex.org/W2899201819","https://openalex.org/W2939384298","https://openalex.org/W2942368658","https://openalex.org/W2947185073","https://openalex.org/W2948515602","https://openalex.org/W2949023359","https://openalex.org/W2949634581","https://openalex.org/W2951261569","https://openalex.org/W2951660448","https://openalex.org/W2953139137","https://openalex.org/W2953941229","https://openalex.org/W2962807143","https://openalex.org/W2962817776","https://openalex.org/W2962864875","https://openalex.org/W2963243172","https://openalex.org/W2963488291","https://openalex.org/W2963619659","https://openalex.org/W2963660453","https://openalex.org/W2963677766","https://openalex.org/W2963911235","https://openalex.org/W2964156315","https://openalex.org/W2964294967","https://openalex.org/W2964325922","https://openalex.org/W2964339842","https://openalex.org/W2964968086","https://openalex.org/W2970562905","https://openalex.org/W2973531541","https://openalex.org/W2980451270","https://openalex.org/W2981518351","https://openalex.org/W2985775862","https://openalex.org/W2988715931","https://openalex.org/W2990578762","https://openalex.org/W3021304778","https://openalex.org/W3102327032","https://openalex.org/W3104726354","https://openalex.org/W6609235337","https://openalex.org/W6685261749","https://openalex.org/W6697658144","https://openalex.org/W6703874418","https://openalex.org/W6703956885","https://openalex.org/W6738279954","https://openalex.org/W6743963275","https://openalex.org/W6747934432","https://openalex.org/W6748862997","https://openalex.org/W6753450616","https://openalex.org/W6754824001","https://openalex.org/W6755934310","https://openalex.org/W6756392615","https://openalex.org/W6758084628","https://openalex.org/W6910769622","https://openalex.org/W6940791371"],"related_works":["https://openalex.org/W3034879369","https://openalex.org/W3011329751","https://openalex.org/W2575575053","https://openalex.org/W2580705004","https://openalex.org/W2950434686","https://openalex.org/W2140950877","https://openalex.org/W324330100","https://openalex.org/W319000773","https://openalex.org/W2253747196","https://openalex.org/W2750078996","https://openalex.org/W2963292632","https://openalex.org/W3048770793","https://openalex.org/W2904859695","https://openalex.org/W1515902347","https://openalex.org/W2922139758","https://openalex.org/W3176180772","https://openalex.org/W2953288645","https://openalex.org/W2803093693","https://openalex.org/W2971225342","https://openalex.org/W2144272357"],"abstract_inverted_index":{"Understanding":[0],"the":[1,23,31,62,82,88,110,156,160],"shape":[2],"of":[3,25,35,64,84,112,182,194,201],"a":[4,7,12,55,106,120,175,192,205],"scene":[5,89],"from":[6,128,155,165],"single":[8,121],"color":[9],"image":[10,123],"is":[11,34,145,185],"formidable":[13],"computer":[14],"vision":[15],"task.":[16,207],"However,":[17],"most":[18],"methods":[19],"aim":[20],"to":[21,30,98,108,140,147],"predict":[22,80,109],"geometry":[24,111],"surfaces":[26],"that":[27,174],"are":[28],"visible":[29,114],"camera,":[32],"which":[33,58,66,79,94,144],"limited":[36],"use":[37,99],"when":[38,52],"planning":[39],"paths":[40],"for":[41,179,204],"robots":[42],"or":[43,92],"augmented":[44],"reality":[45],"agents.":[46],"Such":[47],"agents":[48],"can":[49,68,95],"only":[50],"move":[51],"grounded":[53],"on":[54],"traversable":[56,117],"surface,":[57],"we":[59],"define":[60],"as":[61,73,124],"set":[63],"classes":[65],"humans":[67],"also":[69],"walk":[70],"over,":[71],"such":[72],"grass,":[74],"footpaths":[75],"and":[76,115,137,164,197],"pavement.":[77],"Models":[78],"beyond":[81],"line":[83],"sight":[85],"often":[86],"parameterize":[87],"with":[90],"voxels":[91],"meshes,":[93],"be":[96],"expensive":[97],"in":[100],"machine":[101],"learning":[102],"frameworks.":[103],"We":[104,126,152,172,187],"introduce":[105],"model":[107],"both":[113],"occluded":[116],"surfaces,":[118],"given":[119],"RGB":[122],"input.":[125],"learn":[127],"stereo":[129,170],"video":[130],"sequences,":[131],"using":[132],"camera":[133],"poses,":[134],"per-frame":[135],"depth":[136],"semantic":[138],"segmentation":[139],"form":[141],"training":[142,183],"data,":[143],"used":[146],"supervise":[148],"an":[149,199],"image-to-image":[150],"network.":[151],"train":[153],"models":[154],"KITTI":[157],"driving":[158],"dataset,":[159,163],"indoor":[161],"Matterport":[162],"our":[166,189,202],"own":[167],"casually":[168],"captured":[169],"footage.":[171],"find":[173],"surprisingly":[176],"low":[177],"bar":[178],"spatial":[180],"coverage":[181],"scenes":[184],"required.":[186],"validate":[188],"algorithm":[190],"against":[191],"range":[193],"strong":[195],"baselines,":[196],"include":[198],"assessment":[200],"predictions":[203],"path-planning":[206]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}