{"id":"https://openalex.org/W7161721067","doi":"https://doi.org/10.48550/arxiv.2605.17042","title":"Thermal-Only Crowd Counting with Deployment-Time Privacy Protection","display_name":"Thermal-Only Crowd Counting with Deployment-Time Privacy Protection","publication_year":2026,"publication_date":"2026-05-16","ids":{"openalex":"https://openalex.org/W7161721067","doi":"https://doi.org/10.48550/arxiv.2605.17042"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17042","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17042","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.17042","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136485389","display_name":"Yifei Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian, Yifei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136483588","display_name":"Zhongliang Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Zhongliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113407755","display_name":"Chun Tong Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei, Chun Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136490708","display_name":"Bowen Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Bowen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041734550","display_name":"Chun Pong Lau","orcid":"https://orcid.org/0000-0003-3748-4160"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lau, Chun Pong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136472795","display_name":"Xiaopeng Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Xiaopeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5072892248","display_name":"Michael P. Pound","orcid":"https://orcid.org/0000-0002-5016-1078"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pound, Michael P.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.7208999991416931,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.7208999991416931,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.08910000324249268,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.04670000076293945,"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/discriminative-model","display_name":"Discriminative model","score":0.680400013923645},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.657800018787384},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6452000141143799},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.5006999969482422},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47870001196861267},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.4690000116825104},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.3752000033855438},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.35760000348091125}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7164999842643738},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.680400013923645},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.657800018787384},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6452000141143799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5059999823570251},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.5006999969482422},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47870001196861267},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4690000116825104},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.35760000348091125},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3407000005245209},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2752000093460083},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.265500009059906},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C2778656907","wikidata":"https://www.wikidata.org/wiki/Q5164712","display_name":"Consumer privacy","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17042","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17042","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.17042","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17042","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":"article"},"sustainable_development_goals":[{"score":0.6597083806991577,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"RGB-Thermal":[1],"crowd":[2,36],"counting":[3,114],"has":[4],"shown":[5],"promise,":[6],"the":[7,28,47,91,95,106,141,149],"paradigm":[8],"faces":[9],"critical":[10],"limitations:":[11],"RGB":[12,39,53,145],"data":[13],"raises":[14],"privacy":[15,48,151],"concerns":[16],"in":[17,55,153],"public":[18,56],"surveillance,":[19],"and":[20,44,109,119],"multi-modal":[21],"misalignment":[22],"degrades":[23],"fusion":[24,131],"performance.":[25],"We":[26],"propose":[27],"first":[29],"thermal-only":[30],"framework":[31],"specifically":[32],"designed":[33],"for":[34,143],"privacy-conscious":[35],"counting,":[37],"eliminating":[38,140],"dependency":[40],"at":[41],"inference":[42],"time":[43],"substantially":[45],"reducing":[46],"exposure":[49],"associated":[50],"with":[51],"continuous":[52,144],"capture":[54,146],"surveillance":[57,155],"deployments.":[58],"To":[59],"mitigate":[60],"thermal":[61,77,136],"ambiguity,":[62],"we":[63,80],"leverage":[64],"depth-to-RGB":[65],"diffusion":[66],"models":[67],"as":[68],"a":[69],"cross-modal":[70],"bridge,":[71],"extracting":[72],"discriminative":[73],"features":[74,87,104],"that":[75,82,112,147],"enhance":[76],"representations.":[78],"Critically,":[79],"demonstrate":[81],"single-step":[83],"LCM":[84],"denoising":[85],"yields":[86],"most":[88],"faithful":[89],"to":[90],"structural":[92],"content":[93],"of":[94],"depth":[96],"conditioning":[97,107],"signal,":[98],"while":[99,133],"multi-step":[100],"approaches":[101],"progressively":[102],"decouple":[103],"from":[105],"input":[108,137],"accumulate":[110],"errors":[111],"degrade":[113],"accuracy.":[115],"Experiments":[116],"on":[117],"RGBT-CC":[118],"DroneRGBT":[120],"datasets":[121],"show":[122],"our":[123],"method":[124],"achieves":[125],"competitive":[126],"performance":[127],"against":[128],"state-of-the-art":[129],"RGB-T":[130],"methods,":[132],"requiring":[134],"only":[135],"during":[138],"inference,":[139],"need":[142],"constitutes":[148],"primary":[150],"concern":[152],"real-world":[154],"deployment.":[156],"The":[157],"code":[158],"will":[159],"be":[160],"made":[161],"publicly":[162],"available.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-20T00:00:00"}
