WE2.R9.2
SEMANTIC PRIOR-GUIDED WEAKLY SUPERVISED BUILDING CHANGE DETECTION WITH FOUNDATION MODELS
Wenqi Zhou, Jia Liu, Wenhua Zhang, Fang Liu, Jingxiang Yang, Liang Xiao, Nanjing University of Science and Technology, China
Session:
WE2.R9: Deep Learning for Change Detection Oral
Track:
Theory and Techniques
Location:
TBD
Presentation Time:
Wed, 12 Aug, 11:15 - 11:30
Presentation
Discussion
Resources
No resources available.
Session WE2.R9
WE2.R9.1: COUNTERFACTUAL-GUIDED CONTRASTIVE LEARNING FOR ROBUST CHANGE DETECTION
Ouga Ishibashi, Keijiro Ozaki, Jin Nakazawa, Keio University, Japan
WE2.R9.2: SEMANTIC PRIOR-GUIDED WEAKLY SUPERVISED BUILDING CHANGE DETECTION WITH FOUNDATION MODELS
Wenqi Zhou, Jia Liu, Wenhua Zhang, Fang Liu, Jingxiang Yang, Liang Xiao, Nanjing University of Science and Technology, China
WE2.R9.3: LDGUID: A FRAMEWORK FOR ROBUST CHANGE DETECTION VIA LATENT DIFFERENCE GUIDANCE
Jiaxuan Zhao, Ali Bereyhi, University of Toronto, Canada
WE2.R9.4: REMOTEVAR: AUTOREGRESSIVE VISUAL MODELING FOR REMOTE SENSING CHANGE DETECTION
Yilmaz Korkmaz, Vishal M. Patel, Johns Hopkins University, United States
WE2.R9.5: PMI-NET: PROGRESSIVE MODAL INTERACTION NETWORK FOR REMOTE SENSING IMAGE CHANGE CAPTIONING
Zhongqian Jin, Xi'an Research Institute of Navigation Technology, China; Xuze Dong, Yingping Han, Lirong Han, Kaiqi Xu, Shuang Wang, Xidian University, China
Contacts