{"id":"https://openalex.org/W7147458409","doi":"https://doi.org/10.48550/arxiv.2603.27238","title":"An Instance-Centric Panoptic Occupancy Prediction Benchmark for Autonomous Driving","display_name":"An Instance-Centric Panoptic Occupancy Prediction Benchmark for Autonomous Driving","publication_year":2026,"publication_date":"2026-03-28","ids":{"openalex":"https://openalex.org/W7147458409","doi":"https://doi.org/10.48550/arxiv.2603.27238"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.27238","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27238","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.27238","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132560202","display_name":"Yi Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Feng, Yi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132589170","display_name":"Junwu E","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"E, Junwu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101395423","display_name":"Zizhan Guo","orcid":"https://orcid.org/0009-0003-7360-2192"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Zizhan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132565296","display_name":"Yu Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Yu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132635513","display_name":"Hanli Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Hanli","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132580024","display_name":"Rui Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Rui","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5132560202"],"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.3815000057220459,"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":0.3815000057220459,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.26420000195503235,"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":0.17810000479221344,"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/occupancy","display_name":"Occupancy","score":0.869700014591217},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7056999802589417},{"id":"https://openalex.org/keywords/occupancy-grid-mapping","display_name":"Occupancy grid mapping","score":0.6699000000953674},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5407999753952026},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.43309998512268066},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.3862999975681305},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.33629998564720154},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.31619998812675476}],"concepts":[{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.869700014591217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7134000062942505},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7056999802589417},{"id":"https://openalex.org/C57077369","wikidata":"https://www.wikidata.org/wiki/Q7075747","display_name":"Occupancy grid mapping","level":4,"score":0.6699000000953674},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5407999753952026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4661000072956085},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35589998960494995},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3456000089645386},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.33629998564720154},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3107999861240387},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C2778597888","wikidata":"https://www.wikidata.org/wiki/Q172169","display_name":"3D city models","level":3,"score":0.2831999957561493},{"id":"https://openalex.org/C138569888","wikidata":"https://www.wikidata.org/wiki/Q828310","display_name":"Panopticon","level":3,"score":0.2809000015258789},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.27238","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27238","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":"doi:10.48550/arxiv.2603.27238","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27238","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Panoptic":[0],"occupancy":[1,38,83,126,142,165],"prediction":[2,84],"aims":[3],"to":[4,159],"jointly":[5],"infer":[6],"voxel-wise":[7],"semantics":[8],"and":[9,35,45,65,110,188,199],"instance":[10],"identities":[11],"within":[12],"a":[13,121,168,182],"unified":[14,92,183],"3D":[15,30,67,81,93,105,195],"scene":[16],"representation.":[17],"Nevertheless,":[18],"progress":[19],"in":[20,191],"this":[21,73],"field":[22,193],"remains":[23],"constrained":[24],"by":[25],"the":[26,52,80,90,130,161,177,192],"absence":[27],"of":[28,54,57,163,171,194],"high-quality":[29,104],"mesh":[31,94],"resources,":[32],"instance-level":[33,49,141],"annotations,":[34,50],"physically":[36,123],"consistent":[37,124],"datasets.":[39,166],"Existing":[40],"benchmarks":[41],"typically":[42],"provide":[43],"incomplete":[44],"low-resolution":[46],"geometry":[47],"without":[48],"limiting":[51],"development":[53],"models":[55,106,173],"capable":[56],"achieving":[58],"precise":[59],"geometric":[60],"reconstruction,":[61],"reliable":[62],"occlusion":[63],"reasoning,":[64],"holistic":[66],"understanding.":[68],"To":[69],"address":[70],"these":[71],"challenges,":[72],"paper":[74],"presents":[75],"an":[76],"instance-centric":[77],"benchmark":[78,170],"for":[79,97,185],"panoptic":[82,125,196],"task.":[85],"Specifically,":[86],"we":[87,117],"introduce":[88],"ADMesh,":[89,116],"first":[91],"library":[95],"tailored":[96],"autonomous":[98],"driving,":[99],"which":[100,180],"integrates":[101],"over":[102,136],"15K":[103],"with":[107,139],"diverse":[108],"textures":[109],"rich":[111],"semantic":[112],"annotations.":[113],"Building":[114],"upon":[115],"further":[118],"construct":[119],"CarlaOcc,":[120],"large-scale,":[122],"dataset":[127,134,200],"generated":[128],"using":[129],"CARLA":[131],"simulator.":[132],"This":[133],"contains":[135],"100K":[137],"frames":[138],"fine-grained,":[140],"ground":[143],"truth":[144],"at":[145,203],"voxel":[146],"resolutions":[147],"as":[148,150],"fine":[149],"0.05":[151],"m.":[152],"Furthermore,":[153],"standardized":[154],"evaluation":[155],"metrics":[156],"are":[157,201],"introduced":[158],"quantify":[160],"quality":[162],"existing":[164],"Finally,":[167],"systematic":[169],"representative":[172],"is":[174],"established":[175],"on":[176],"proposed":[178],"dataset,":[179],"provides":[181],"platform":[184],"fair":[186],"comparison":[187],"reproducible":[189],"research":[190],"perception.":[197],"Code":[198],"available":[202],"https://mias.group/CarlaOcc.":[204]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}
