{"id":"https://openalex.org/W4416061282","doi":"https://doi.org/10.1109/iccv51701.2025.01444","title":"SPADE: Spatial-Aware Denoising Network for Open-Vocabulary Panoptic Scene Graph Generation with Long- and Local-Range Context Reasoning","display_name":"SPADE: Spatial-Aware Denoising Network for Open-Vocabulary Panoptic Scene Graph Generation with Long- and Local-Range Context Reasoning","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416061282","doi":"https://doi.org/10.1109/iccv51701.2025.01444"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.05798","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101916472","display_name":"Xin Hu","orcid":"https://orcid.org/0000-0001-6094-8571"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Hu","raw_affiliation_strings":["The Laboratory of Intelligent Collaborative Computing of UESTC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Laboratory of Intelligent Collaborative Computing of UESTC","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106406508","display_name":"Ke Qin","orcid":"https://orcid.org/0009-0004-7557-2887"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Qin","raw_affiliation_strings":["The Laboratory of Intelligent Collaborative Computing of UESTC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Laboratory of Intelligent Collaborative Computing of UESTC","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081385896","display_name":"Guiduo Duan","orcid":"https://orcid.org/0000-0001-6857-7744"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guiduo Duan","raw_affiliation_strings":["The Laboratory of Intelligent Collaborative Computing of UESTC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Laboratory of Intelligent Collaborative Computing of UESTC","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351321","display_name":"Ming Li","orcid":"https://orcid.org/0000-0001-6291-9328"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017943466","display_name":"Yuan-Fang Li","orcid":"https://orcid.org/0000-0003-4651-2821"},"institutions":[{"id":"https://openalex.org/I2801239119","display_name":"Australian Regenerative Medicine Institute","ror":"https://ror.org/02qa5kg76","country_code":"AU","type":"facility","lineage":["https://openalex.org/I2801037857","https://openalex.org/I2801239119","https://openalex.org/I56590836"]},{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yuan-Fang Li","raw_affiliation_strings":["Monash University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Monash University","institution_ids":["https://openalex.org/I2801239119","https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100761497","display_name":"Tao He","orcid":"https://orcid.org/0000-0001-8676-7429"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao He","raw_affiliation_strings":["The Laboratory of Intelligent Collaborative Computing of UESTC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Laboratory of Intelligent Collaborative Computing of UESTC","institution_ids":["https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":"15562","last_page":"15572"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9768999814987183,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9768999814987183,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.004100000020116568,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.004100000020116568,"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/relation","display_name":"Relation (database)","score":0.5903000235557556},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49570000171661377},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.489300012588501},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4352000057697296},{"id":"https://openalex.org/keywords/spatial-relation","display_name":"Spatial relation","score":0.38429999351501465},{"id":"https://openalex.org/keywords/scene-graph","display_name":"Scene graph","score":0.35260000824928284},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3517000079154968}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6504999995231628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6057999730110168},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5903000235557556},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49570000171661377},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.489300012588501},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4352000057697296},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C179372163","wikidata":"https://www.wikidata.org/wiki/Q1406181","display_name":"Scene graph","level":3,"score":0.35260000824928284},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.351500004529953},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.34290000796318054},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3424000144004822},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.335099995136261},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3264999985694885},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2721000015735626},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27160000801086426},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2599000036716461}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2507.05798","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.05798","pdf_url":"https://arxiv.org/pdf/2507.05798","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2507.05798","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.05798","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":"pmh:oai:arXiv.org:2507.05798","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.05798","pdf_url":"https://arxiv.org/pdf/2507.05798","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6966311521","display_name":null,"funder_award_id":"62306064","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Panoptic":[0],"Scene":[1],"Graph":[2],"Generation":[3],"(PSG)":[4],"integrates":[5],"instance":[6],"segmentation":[7],"with":[8,125],"relation":[9,45,59,145,161],"understanding":[10],"to":[11],"capture":[12],"pixel-level":[13],"structural":[14],"relationships":[15],"in":[16,31,43,50,57,69,178],"complex":[17],"scenes.":[18],"Although":[19],"recent":[20],"approaches":[21],"leveraging":[22],"pre-trained":[23,116],"vision-language":[24],"models":[25],"(VLMs)":[26],"have":[27],"significantly":[28],"improved":[29],"performance":[30],"the":[32,38,63,71,100,109,138,157],"open-vocabulary":[33,88],"setting,":[34],"they":[35],"commonly":[36],"ignore":[37],"inherent":[39],"limitations":[40],"of":[41,74,92,159],"VLMs":[42],"spatial":[44,72,186],"reasoning,":[46],"such":[47],"as":[48],"difficulty":[49],"distinguishing":[51],"object":[52],"relative":[53],"positions,":[54],"which":[55],"results":[56],"suboptimal":[58],"prediction.":[60,188],"Motivated":[61],"by":[62],"denoising":[64,123],"diffusion":[65,118],"model's":[66],"inversion":[67,130],"process":[68],"preserving":[70],"structure":[73],"input":[75],"images,":[76],"we":[77,112,141],"propose":[78],"SPADE":[79,90,174],"(SPatial-Aware":[80],"Denoising-nEtwork)":[81],"framework":[82],"--":[83],"a":[84,114,121,132,143],"novel":[85],"approach":[86],"for":[87,99,185],"PSG.":[89],"consists":[91],"two":[93],"key":[94],"steps:":[95],"(1)":[96],"inversion-guided":[97],"calibration":[98],"UNet":[101],"adaptation,":[102],"and":[103,152,168,181],"(2)":[104],"spatial-aware":[105,144],"context":[106],"reasoning.":[107],"In":[108,137],"first":[110],"step,":[111,140],"calibrate":[113],"general":[115],"teacher":[117],"model":[119],"into":[120],"PSG-specific":[122],"network":[124],"cross-attention":[126],"maps":[127],"derived":[128],"during":[129],"through":[131],"lightweight":[133],"LoRA-based":[134],"fine-tuning":[135],"strategy.":[136],"second":[139],"develop":[142],"graph":[146],"transformer":[147],"that":[148,173],"captures":[149],"both":[150,179],"local":[151],"long-range":[153],"contextual":[154],"information,":[155],"facilitating":[156],"generation":[158],"high-quality":[160],"queries.":[162],"Extensive":[163],"experiments":[164],"on":[165],"benchmark":[166],"PSG":[167],"Visual":[169],"Genome":[170],"datasets":[171],"demonstrate":[172],"outperforms":[175],"state-of-the-art":[176],"methods":[177],"closed-":[180],"open-set":[182],"scenarios,":[183],"particularly":[184],"relationship":[187]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
