{"id":"https://openalex.org/W4417032776","doi":"https://doi.org/10.48550/arxiv.2512.03837","title":"Heatmap Pooling Network for Action Recognition from RGB Videos","display_name":"Heatmap Pooling Network for Action Recognition from RGB Videos","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W4417032776","doi":"https://doi.org/10.48550/arxiv.2512.03837"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.03837","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.03837","pdf_url":"https://arxiv.org/pdf/2512.03837","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.03837","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100705472","display_name":"Mengyuan Liu","orcid":"https://orcid.org/0000-0002-6332-8316"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liu, Mengyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101763629","display_name":"Jinfu Liu","orcid":"https://orcid.org/0000-0002-4590-5343"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jinfu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102944675","display_name":"Yongkang Jiang","orcid":"https://orcid.org/0000-0002-2768-6159"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yongkang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5049557511","display_name":"Bin He","orcid":"https://orcid.org/0000-0003-3193-6269"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Bin","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100705472"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9891999959945679,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9891999959945679,"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/T12290","display_name":"Human Motion and Animation","score":0.00139999995008111,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/rgb-color-model","display_name":"RGB color model","score":0.7936000227928162},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7384999990463257},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5059000253677368},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.4771000146865845},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4498000144958496},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42800000309944153},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4041000008583069},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.38600000739097595},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3700999915599823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8109999895095825},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.7936000227928162},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7384999990463257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7067999839782715},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5059000253677368},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.4771000146865845},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4498000144958496},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42800000309944153},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37299999594688416},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3700999915599823},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3398999869823456},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3206999897956848},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3075000047683716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2888000011444092},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2705000042915344},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.03837","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.03837","pdf_url":"https://arxiv.org/pdf/2512.03837","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.03837","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.03837","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":"pmh:oai:arXiv.org:2512.03837","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.03837","pdf_url":"https://arxiv.org/pdf/2512.03837","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417032776.pdf","grobid_xml":"https://content.openalex.org/works/W4417032776.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Human":[0],"action":[1,62,131,160],"recognition":[2,63,161],"(HAR)":[3],"in":[4,15,51,78],"videos":[5,27,79],"has":[6],"garnered":[7],"widespread":[8],"attention":[9],"due":[10],"to":[11,35,118],"the":[12,48,75,94,120,150,157],"rich":[13],"information":[14,32,50],"RGB":[16,26],"videos.":[17,103],"Nevertheless,":[18],"existing":[19,158],"methods":[20],"for":[21,61],"extracting":[22],"deep":[23],"features":[24,73,88,101,123],"from":[25,64,102],"face":[28],"challenges":[29],"such":[30],"as":[31],"redundancy,":[33],"susceptibility":[34],"noise":[36],"and":[37,45,70,99,112,146],"high":[38],"storage":[39],"costs.":[40],"To":[41],"address":[42],"these":[43],"issues":[44],"fully":[46],"harness":[47],"useful":[49],"videos,":[52,65],"we":[53,106],"propose":[54],"a":[55,81,108,113],"novel":[56],"heatmap":[57,100],"pooling":[58,83],"network":[59],"(HP-Net)":[60],"which":[66,155],"extracts":[67],"information-rich,":[68],"robust":[69,130],"concise":[71],"pooled":[72,87,122],"of":[74,152],"human":[76,159],"body":[77],"through":[80],"feedback":[82],"module.":[84],"The":[85],"extracted":[86,121],"demonstrate":[89],"obvious":[90],"performance":[91],"advantages":[92],"over":[93],"previously":[95],"obtained":[96],"pose":[97],"data":[98],"In":[104],"addition,":[105],"design":[107],"spatial-motion":[109],"co-learning":[110],"module":[111,117],"text":[114],"refinement":[115],"modulation":[116],"integrate":[119],"with":[124],"other":[125],"multimodal":[126],"data,":[127],"enabling":[128],"more":[129],"recognition.":[132],"Extensive":[133],"experiments":[134],"on":[135],"several":[136],"benchmarks":[137],"namely":[138],"NTU":[139,142],"RGB+D":[140,143],"60,":[141],"120,":[144],"Toyota-Smarthome":[145],"UAV-Human":[147],"consistently":[148],"verify":[149],"effectiveness":[151],"our":[153],"HP-Net,":[154],"outperforms":[156],"methods.":[162],"Our":[163],"code":[164],"is":[165],"publicly":[166],"available":[167],"at:":[168],"https://github.com/liujf69/HPNet-Action.":[169]},"counts_by_year":[],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-12-05T00:00:00"}
