{"id":"https://openalex.org/W4416749362","doi":"https://doi.org/10.1109/iros60139.2025.11246274","title":"RDN: An Efficient Denoising Network for 4D Radar Point Clouds","display_name":"RDN: An Efficient Denoising Network for 4D Radar Point Clouds","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416749362","doi":"https://doi.org/10.1109/iros60139.2025.11246274"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11246274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246274","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":"article","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/A5109717247","display_name":"Ningyuan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ningyuan Huang","raw_affiliation_strings":["Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100765836","display_name":"Zhiheng Li","orcid":"https://orcid.org/0000-0002-1477-2066"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Li","raw_affiliation_strings":["Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081929787","display_name":"Chenglin Pang","orcid":"https://orcid.org/0000-0001-6032-2448"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenglin Pang","raw_affiliation_strings":["Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101808083","display_name":"Zheng Fang","orcid":"https://orcid.org/0000-0002-3762-754X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Fang","raw_affiliation_strings":["Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31907768,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9862","last_page":"9869"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.45210000872612,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.45210000872612,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.09780000150203705,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.06639999896287918,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8011999726295471},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.6402000188827515},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6378999948501587},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5580999851226807},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5521000027656555},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5425999760627747},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.42739999294281006},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.32710000872612},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.3264000117778778}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8011999726295471},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.682699978351593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6470000147819519},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.6402000188827515},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6378999948501587},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5580999851226807},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5521000027656555},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5436999797821045},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5425999760627747},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.3264000117778778},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.3255000114440918},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.325300008058548},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2802000045776367},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.26989999413490295},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.2529999911785126},{"id":"https://openalex.org/C174440990","wikidata":"https://www.wikidata.org/wiki/Q681349","display_name":"Point-to-point","level":2,"score":0.2524000108242035},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11246274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246274","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":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2152864241","https://openalex.org/W2905253977","https://openalex.org/W2906788812","https://openalex.org/W2962912109","https://openalex.org/W2979750740","https://openalex.org/W2990613095","https://openalex.org/W3003437478","https://openalex.org/W3005974859","https://openalex.org/W3093434340","https://openalex.org/W3109154950","https://openalex.org/W3134385809","https://openalex.org/W3173916380","https://openalex.org/W3177330511","https://openalex.org/W3181190968","https://openalex.org/W3212045733","https://openalex.org/W4206979414","https://openalex.org/W4210423514","https://openalex.org/W4214755140","https://openalex.org/W4249866455","https://openalex.org/W4285303928","https://openalex.org/W4287025408","https://openalex.org/W4311437690","https://openalex.org/W4312586511","https://openalex.org/W4313183789","https://openalex.org/W4365420566","https://openalex.org/W4383200248","https://openalex.org/W4385800972","https://openalex.org/W4386038339","https://openalex.org/W4386083014","https://openalex.org/W4391768470","https://openalex.org/W4393032756","https://openalex.org/W4393153707","https://openalex.org/W4400771235","https://openalex.org/W4401416948","https://openalex.org/W4402592730","https://openalex.org/W4405270187"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"point":[1,18,77,90,114,177],"cloud":[2,19,178],"information":[3,139],"is":[4],"important":[5],"for":[6,54,138],"robot":[7,182],"perception":[8],"and":[9,102,118,158,164],"autonomous":[10],"driving.":[11],"Although":[12],"advanced":[13],"4D":[14,55,106],"radar":[15,69,107],"can":[16,82],"provide":[17],"with":[20],"higher":[21],"resolution":[22],"than":[23],"3D":[24],"radar,":[25],"its":[26],"data":[27],"still":[28],"contains":[29],"a":[30,49,73,111],"significant":[31],"amount":[32],"of":[33,68,105,166,176],"noise":[34],"due":[35],"to":[36,63,93,134,149],"measurement":[37],"principle.":[38],"To":[39],"solve":[40],"this":[41],"issue,":[42],"we":[43,71,109],"propose":[44],"RDN":[45,57],"(Radar":[46],"Denoising":[47],"Network),":[48],"denoising":[50,179],"network":[51,133],"specifically":[52],"designed":[53],"radar.":[56],"includes":[58],"three":[59],"innovative":[60],"modules:":[61],"First,":[62],"overcome":[64],"the":[65,88,100,132,142,162,173],"noisy":[66,89],"nature":[67],"points,":[70,108],"design":[72],"feature":[74,95,113,129,152],"similarity-based":[75],"farthest":[76],"sampling":[78,85],"module":[79,117,126,144],"(FS-FPS),":[80],"which":[81],"extract":[83],"representative":[84],"points":[86,130],"from":[87],"cloud.":[91],"Secondly,":[92],"address":[94],"propagation":[96],"issues":[97],"caused":[98],"by":[99],"sparse":[101],"long-range":[103],"characteristics":[104],"introduce":[110],"virtual":[112,128],"prediction":[115],"(VFP)":[116],"an":[119,146],"iterative":[120,147],"upsampling":[121],"(IUS)":[122],"module.":[123],"The":[124,154],"VFP":[125],"generates":[127],"through":[131],"serve":[135],"as":[136],"bridges":[137],"transmission,":[140],"while":[141],"IUS":[143],"uses":[145],"approach":[148],"gradually":[150],"refine":[151],"propagation.":[153],"experiments":[155,171],"on":[156],"MSC-RAD4D":[157],"NTU4DRadLM":[159],"datasets":[160],"demonstrate":[161],"effectiveness":[163],"generalization":[165],"our":[167],"method.":[168],"Besides,":[169],"odometry":[170],"prove":[172],"practical":[174],"value":[175],"in":[180],"improving":[181],"perception.":[183]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-11-28T00:00:00"}
