{"id":"https://openalex.org/W7160945487","doi":"https://doi.org/10.48550/arxiv.2605.10117","title":"Think as Needed: Geometry-Driven Adaptive Perception for Autonomous Driving","display_name":"Think as Needed: Geometry-Driven Adaptive Perception for Autonomous Driving","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160945487","doi":"https://doi.org/10.48550/arxiv.2605.10117"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.10117","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10117","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.10117","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135970718","display_name":"Donghyun Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Donghyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5062741658","display_name":"Jaehyoung Park","orcid":"https://orcid.org/0000-0002-2644-9151"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Jaehyoung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4474000036716461,"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":0.4474000036716461,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.16009999811649323,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.04390000179409981,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.5778999924659729},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.42669999599456787},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.41909998655319214},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.41499999165534973},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.38909998536109924},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.3808000087738037},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.35850000381469727},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.35690000653266907},{"id":"https://openalex.org/keywords/quadratic-growth","display_name":"Quadratic growth","score":0.3508000075817108}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.671500027179718},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5778999924659729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5110999941825867},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5091000199317932},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.42669999599456787},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41909998655319214},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.41499999165534973},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.38909998536109924},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.3808000087738037},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.35690000653266907},{"id":"https://openalex.org/C195956108","wikidata":"https://www.wikidata.org/wiki/Q7268362","display_name":"Quadratic growth","level":2,"score":0.3508000075817108},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.30059999227523804},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C136085584","wikidata":"https://www.wikidata.org/wiki/Q910289","display_name":"Overlay","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.25450000166893005},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.25220000743865967},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.10117","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10117","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.10117","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10117","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.6105546355247498,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"driving":[1],"scenes":[2,33,188],"range":[3],"from":[4,138,172],"empty":[5],"highways":[6],"to":[7,26,62,164],"dense":[8],"intersections":[9],"with":[10,50,120,189],"dozens":[11],"of":[12,53,84],"interacting":[13],"road":[14],"users,":[15],"yet":[16],"current":[17],"3D":[18],"detection":[19],"models":[20,47],"apply":[21],"a":[22,98,121,146],"fixed":[23],"computation":[24],"budget":[25],"every":[27],"frame,":[28],"wasting":[29],"resources":[30,144],"on":[31,186,200],"simple":[32,187],"while":[34],"lacking":[35],"capacity":[36],"for":[37,145],"complex":[38],"ones.":[39],"Existing":[40],"approaches":[41],"compound":[42],"this":[43],"problem:":[44],"Transformer-based":[45],"interaction":[46,112],"scale":[48],"quadratically":[49],"the":[51,60,66,81,162,175],"number":[52],"detected":[54,154],"objects,":[55],"and":[56,94,131,156,177,204],"frame-by-frame":[57],"processing":[58,102],"causes":[59],"system":[61,163],"immediately":[63],"forget":[64],"objects":[65,128,155,167,206],"moment":[67],"they":[68,170],"become":[69],"occluded.":[70],"We":[71],"propose":[72],"Enhanced":[73,180],"HOPE,":[74],"an":[75,90],"adaptive":[76],"perception":[77],"architecture":[78],"that":[79,125,151],"measures":[80],"geometric":[82],"complexity":[83],"each":[85],"incoming":[86],"LiDAR":[87],"frame":[88],"using":[89],"unsupervised":[91],"statistical":[92],"estimator":[93],"routes":[95],"it":[96],"through":[97,207],"shallow":[99],"or":[100],"deep":[101],"path":[103],"accordingly,":[104],"requiring":[105],"no":[106,190],"manual":[107],"scene":[108],"labels.":[109],"To":[110],"keep":[111],"modeling":[113],"efficient,":[114],"we":[115],"replace":[116],"quadratic":[117],"pairwise":[118],"attention":[119],"linear-time":[122],"subspace-based":[123],"network":[124],"groups":[126],"nearby":[127],"into":[129],"clusters":[130],"processes":[132],"them":[133],"jointly.":[134],"The":[135],"computational":[136],"savings":[137],"these":[139],"two":[140],"mechanisms":[141],"free":[142],"up":[143],"persistent":[147],"temporal":[148],"memory":[149],"module":[150],"retains":[152],"previously":[153],"traffic":[157],"rules":[158],"across":[159],"frames,":[160],"enabling":[161],"recall":[165],"occluded":[166],"seconds":[168],"after":[169],"disappear":[171],"view.":[173],"On":[174],"nuScenes":[176],"CARLA":[178],"benchmarks,":[179],"HOPE":[181],"reduces":[182],"latency":[183],"by":[184,197],"38%":[185],"accuracy":[191],"loss,":[192],"improves":[193],"mean":[194],"Average":[195],"Precision":[196],"2.7":[198],"points":[199],"rare":[201],"long-tail":[202],"scenarios,":[203],"tracks":[205],"occlusions":[208],"lasting":[209],"over":[210],"5":[211],"seconds,":[212],"where":[213],"all":[214],"tested":[215],"baselines":[216],"fail.":[217]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}