{"id":"https://openalex.org/W4389665731","doi":"https://doi.org/10.1109/iros55552.2023.10342521","title":"Visual Pre-Training for Navigation: What Can We Learn from Noise?","display_name":"Visual Pre-Training for Navigation: What Can We Learn from Noise?","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4389665731","doi":"https://doi.org/10.1109/iros55552.2023.10342521"},"language":"en","primary_location":{"id":"doi:10.1109/iros55552.2023.10342521","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iros55552.2023.10342521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100642501","display_name":"Yanwei Wang","orcid":"https://orcid.org/0000-0002-2560-2150"},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Yanwei Wang","raw_affiliation_strings":["MIT,Department of Electrical Engineering and Computer Science","Department of Electrical Engineering and Computer Science, MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT,Department of Electrical Engineering and Computer Science","institution_ids":["https://openalex.org/I4210109586"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, MIT","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030063621","display_name":"Ching-Yun Ko","orcid":"https://orcid.org/0000-0002-8966-8570"},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Ching-Yun Ko","raw_affiliation_strings":["MIT,Department of Electrical Engineering and Computer Science","Department of Electrical Engineering and Computer Science, MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT,Department of Electrical Engineering and Computer Science","institution_ids":["https://openalex.org/I4210109586"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, MIT","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111774389","display_name":"Pulkit Agrawal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Pulkit Agrawal","raw_affiliation_strings":["MIT,Department of Electrical Engineering and Computer Science","Department of Electrical Engineering and Computer Science, MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT,Department of Electrical Engineering and Computer Science","institution_ids":["https://openalex.org/I4210109586"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, MIT","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210109586"],"apc_list":null,"apc_paid":null,"fwci":0.4356,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.62339808,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"34","issue":null,"first_page":"3897","last_page":"3902"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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":0.7812256813049316},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6940619349479675},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6874912977218628},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5328662395477295},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.527684211730957},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5237674117088318},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4960575997829437},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4642634391784668},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3598288893699646},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32414788007736206},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1589098572731018}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7812256813049316},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6940619349479675},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6874912977218628},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5328662395477295},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.527684211730957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5237674117088318},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4960575997829437},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4642634391784668},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3598288893699646},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32414788007736206},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1589098572731018},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros55552.2023.10342521","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iros55552.2023.10342521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W343636949","https://openalex.org/W2201912979","https://openalex.org/W2326925005","https://openalex.org/W2912269676","https://openalex.org/W2953127211","https://openalex.org/W2962785568","https://openalex.org/W2963420272","https://openalex.org/W2963826423","https://openalex.org/W2964021598","https://openalex.org/W2989731761","https://openalex.org/W3006398608","https://openalex.org/W3009928773","https://openalex.org/W3035524453","https://openalex.org/W3115293622","https://openalex.org/W3137182587","https://openalex.org/W3159481202","https://openalex.org/W4213414377","https://openalex.org/W4287121556","https://openalex.org/W4385245566","https://openalex.org/W6720501231","https://openalex.org/W6739901393","https://openalex.org/W6774314701","https://openalex.org/W6775634482","https://openalex.org/W6787713516"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4394050964","https://openalex.org/W2551249631"],"abstract_inverted_index":{"One":[0],"powerful":[1],"paradigm":[2],"in":[3,85],"visual":[4],"navigation":[5,53,110],"is":[6,119],"to":[7,24,73,96,107],"predict":[8],"actions":[9],"from":[10],"observations":[11],"directly.":[12],"Training":[13],"such":[14,81],"an":[15],"end-to-end":[16],"system":[17,35],"allows":[18],"representations":[19],"useful":[20],"for":[21,51],"downstream":[22],"tasks":[23],"emerge":[25],"automatically.":[26],"However,":[27],"the":[28,44,48,60,68,74],"lack":[29],"of":[30,43,64,67],"inductive":[31],"bias":[32],"makes":[33],"this":[34],"data":[36],"inefficient.":[37],"We":[38,76],"hypothesize":[39],"a":[40,52,65,86,109],"sufficient":[41],"representation":[42,102],"current":[45,69],"view":[46,50,70],"and":[47,62],"goal":[49],"policy":[54,111],"can":[55,103],"be":[56,105],"learned":[57,101],"by":[58],"predicting":[59],"location":[61],"size":[63],"crop":[66,83],"that":[71,79],"corresponds":[72],"goal.":[75],"further":[77],"show":[78],"training":[80],"random":[82],"prediction":[84],"self-supervised":[87],"fashion":[88],"purely":[89],"on":[90],"synthetic":[91],"noise":[92],"images":[93],"transfers":[94],"well":[95],"natural":[97],"home":[98],"images.":[99],"The":[100,117],"then":[104],"bootstrapped":[106],"learn":[108],"efficiently":[112],"with":[113],"little":[114],"interaction":[115],"data.":[116],"code":[118],"available":[120],"at":[121],"https://yanweiw.github.io/noise2ptz/":[122]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
