{"id":"https://openalex.org/W4416747992","doi":"https://doi.org/10.1109/iros60139.2025.11246202","title":"NGD-SLAM: Towards Real-Time Dynamic SLAM without GPU","display_name":"NGD-SLAM: Towards Real-Time Dynamic SLAM without GPU","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416747992","doi":"https://doi.org/10.1109/iros60139.2025.11246202"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11246202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5107772032","display_name":"Yuhao Zhang","orcid":"https://orcid.org/0009-0003-0573-7335"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yuhao Zhang","raw_affiliation_strings":["University of Manchester"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Manchester","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090898300","display_name":"Mihai Bujanca","orcid":"https://orcid.org/0000-0001-7575-1552"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mihai Bujanca","raw_affiliation_strings":["Qualcomm Technologies XR Labs,Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qualcomm Technologies XR Labs,Austria","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026069638","display_name":"Mikel Luj\u00e1n","orcid":"https://orcid.org/0000-0002-0842-1083"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mikel Luj\u00e1n","raw_affiliation_strings":["University of Manchester"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Manchester","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":51.7228,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.99887537,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3467","last_page":"3473"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9735999703407288,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9735999703407288,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.00559999980032444,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.0038999998942017555,"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/deep-learning","display_name":"Deep learning","score":0.6190999746322632},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5853999853134155},{"id":"https://openalex.org/keywords/laptop","display_name":"Laptop","score":0.5756999850273132},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.47749999165534973},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.4618000090122223},{"id":"https://openalex.org/keywords/tracking-system","display_name":"Tracking system","score":0.38659998774528503},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.38429999351501465},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.3711000084877014}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8483999967575073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6815999746322632},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6190999746322632},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6008999943733215},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5853999853134155},{"id":"https://openalex.org/C2780008327","wikidata":"https://www.wikidata.org/wiki/Q3962","display_name":"Laptop","level":2,"score":0.5756999850273132},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.47749999165534973},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.4618000090122223},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.38659998774528503},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.3711000084877014},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.31290000677108765},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.296999990940094},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2921000123023987},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2741999924182892},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2727999985218048},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11246202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1970504153","https://openalex.org/W1991544872","https://openalex.org/W2020310389","https://openalex.org/W2021851106","https://openalex.org/W2085261163","https://openalex.org/W2091790851","https://openalex.org/W2116442452","https://openalex.org/W2535547924","https://openalex.org/W2745859992","https://openalex.org/W2788608285","https://openalex.org/W2802671577","https://openalex.org/W2808571300","https://openalex.org/W2909157769","https://openalex.org/W2950989657","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963881378","https://openalex.org/W2985926990","https://openalex.org/W3003179103","https://openalex.org/W3043971245","https://openalex.org/W3090298435","https://openalex.org/W3120564201","https://openalex.org/W3206096534","https://openalex.org/W4312606688","https://openalex.org/W4313017528","https://openalex.org/W4390873795","https://openalex.org/W4390874575","https://openalex.org/W4400111956","https://openalex.org/W4400645603","https://openalex.org/W4404370921","https://openalex.org/W4404370967","https://openalex.org/W4405788126","https://openalex.org/W4416057964"],"related_works":[],"abstract_inverted_index":{"Many":[0],"existing":[1,166],"visual":[2],"SLAM":[3,69,160,168],"methods":[4,23],"can":[5],"achieve":[6],"high":[7,130],"localization":[8,131],"accuracy":[9,132],"in":[10,58,133],"dynamic":[11,68,134,159,167],"environments":[12,135],"by":[13,115],"leveraging":[14],"deep":[15,37,89,156],"learning":[16,157],"to":[17,33,40,120,124],"mask":[18,42,81],"moving":[19],"objects.":[20],"However,":[21],"these":[22],"incur":[24],"significant":[25],"computational":[26,118],"overhead":[27],"as":[28],"the":[29,36,152],"camera":[30,86],"tracking":[31,87,100,139],"needs":[32],"wait":[34],"for":[35,51,92,158],"neural":[38],"network":[39],"generate":[41],"at":[43],"each":[44,93],"frame,":[45],"and":[46,88,113],"they":[47],"typically":[48],"require":[49],"GPUs":[50],"realtime":[52],"operation,":[53],"which":[54],"restricts":[55],"their":[56],"practicality":[57],"real-world":[59],"robotic":[60],"applications.":[61],"Therefore,":[62],"this":[63],"paper":[64],"proposes":[65],"a":[66,75,80,98,138,146],"real-time":[67],"system":[70,128],"that":[71,84,102],"runs":[72],"exclusively":[73],"on":[74,145],"CPU.":[76,148],"Our":[77],"approach":[78],"incorporates":[79],"propagation":[82],"mechanism":[83],"decouples":[85],"learning-based":[90],"masking":[91],"frame.":[94],"We":[95],"also":[96],"introduce":[97],"hybrid":[99],"strategy":[101],"integrates":[103],"ORB":[104],"features":[105],"with":[106],"optical":[107],"flow":[108],"methods,":[109,126],"enhancing":[110],"both":[111],"robustness":[112],"efficiency":[114],"selectively":[116],"allocating":[117],"resources":[119],"input":[121],"frames.":[122],"Compared":[123],"previous":[125],"our":[127,175],"maintains":[129],"while":[136],"achieving":[137],"frame":[140],"rate":[141],"of":[142,154],"60":[143],"FPS":[144],"laptop":[147],"These":[149],"results":[150],"demonstrate":[151],"feasibility":[153],"utilizing":[155],"without":[161],"GPU":[162],"support.":[163],"Since":[164],"most":[165],"systems":[169],"are":[170],"not":[171],"open-source,":[172],"we":[173],"make":[174],"code":[176],"publicly":[177],"available":[178],"at:":[179],"https://github.com/yuhaozhang7/NGD-SLAM":[180]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-28T00:00:00"}