{"id":"https://openalex.org/W7140146041","doi":"https://doi.org/10.48550/arxiv.2603.19308","title":"GT-Space: Enhancing Heterogeneous Collaborative Perception with Ground Truth Feature Space","display_name":"GT-Space: Enhancing Heterogeneous Collaborative Perception with Ground Truth Feature Space","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7140146041","doi":"https://doi.org/10.48550/arxiv.2603.19308"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.19308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19308","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.19308","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130379506","display_name":"Wentao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wentao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130345750","display_name":"Haoran Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130325632","display_name":"Guang Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Guang","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":0.3792000114917755,"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":0.3792000114917755,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.18050000071525574,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.06650000065565109,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6771000027656555},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5873000025749207},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5737000107765198},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5644000172615051},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4943000078201294},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.43939998745918274},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41839998960494995},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.41530001163482666},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.41280001401901245}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8136000037193298},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6771000027656555},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5873000025749207},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5737000107765198},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5644000172615051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5412999987602234},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4943000078201294},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.43939998745918274},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43070000410079956},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3982999920845032},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.38589999079704285},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.36719998717308044},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30709999799728394},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2906000018119812},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.19308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19308","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.19308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19308","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"autonomous":[1],"driving,":[2],"multi-agent":[3],"collaborative":[4,72],"perception":[5,73],"enhances":[6],"sensing":[7,30],"capabilities":[8],"by":[9],"enabling":[10],"agents":[11,26,98],"to":[12,105],"share":[13],"perceptual":[14],"data.":[15],"A":[16],"key":[17],"challenge":[18],"lies":[19],"in":[20,59,151],"handling":[21],"{\\em":[22,66],"heterogeneous}":[23],"features":[24],"from":[25,84],"equipped":[27],"with":[28,115,125],"different":[29],"modalities":[31],"or":[32,45],"model":[33],"architectures,":[34],"which":[35],"complicates":[36],"data":[37],"fusion.":[38],"Existing":[39],"approaches":[40],"often":[41],"require":[42],"retraining":[43],"encoders":[44],"designing":[46],"interpreter":[47],"modules":[48],"for":[49,75,91,112],"pairwise":[50,113],"feature":[51,82,92],"alignment,":[52],"but":[53],"these":[54],"solutions":[55],"are":[56],"not":[57],"scalable":[58,71],"practice.":[60],"To":[61],"address":[62],"this,":[63],"we":[64,119],"propose":[65],"GT-Space},":[67],"a":[68,80,88,101,121,141],"flexible":[69],"and":[70,138,140],"framework":[74],"heterogeneous":[76],"agents.":[77,117],"GT-Space":[78,147],"constructs":[79],"common":[81],"space":[83],"ground-truth":[85],"labels,":[86],"providing":[87],"unified":[89],"reference":[90],"alignment.":[93],"With":[94],"this":[95],"shared":[96],"space,":[97],"only":[99],"need":[100,111],"single":[102],"adapter":[103],"module":[104],"project":[106],"their":[107],"features,":[108],"eliminating":[109],"the":[110],"interactions":[114],"other":[116],"Furthermore,":[118],"design":[120],"fusion":[122],"network":[123],"trained":[124],"contrastive":[126],"losses":[127],"across":[128],"diverse":[129],"modality":[130],"combinations.":[131],"Extensive":[132],"experiments":[133],"on":[134],"simulation":[135],"datasets":[136],"(OPV2V":[137],"V2XSet)":[139],"real-world":[142],"dataset":[143],"(RCooper)":[144],"demonstrate":[145],"that":[146],"consistently":[148],"outperforms":[149],"baselines":[150],"detection":[152],"accuracy":[153],"while":[154],"delivering":[155],"robust":[156],"performance.":[157],"Our":[158],"code":[159],"will":[160],"be":[161],"released":[162],"at":[163],"https://github.com/KingScar/GT-Space.":[164]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-24T00:00:00"}
