WE2.P6.4
GENERATIVE VIRTUAL EXEMPLAR LEARNING FOR LABEL-EFFICIENT SATELLITE IMAGE CHANGE DETECTION
Hichem Sahbi, CNRS Sorbonne University, France
Session:
WE2.P6: Deep Learning for Change Detection Oral
Track:
Data Analysis
Location:
Room P6
Presentation Time:
Wednesday, 6 August, 11:15 - 11:30
Presentation
Discussion
Resources
No resources available.
Session WE2.P6
WE2.P6.1: CUTMIX-CD: ADVANCING SEMI-SUPERVISED CHANGE DETECTION VIA MIXED SAMPLE CONSISTENCY
Qidi Shu, Xiaolin Zhu, Luoma Wan, Shuheng Zhao, Denghong Liu, Longkang Peng, Xiaobei Chen, The Hong Kong Polytechnic University, China
WE2.P6.2: HYRET-CHANGE: A HYBRID RETENTIVE NETWORK FOR REMOTE SENSING CHANGE DETECTION
Mustansar Fiaz, IBM Research, United Arab Emirates; Mubashir Noman, Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates; Hiyam Debary, IBM Research, United Arab Emirates; Kamran Ali, FAST National University, Pakistan; Hisham Cholakkal, Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates
WE2.P6.3: CONTRASTIVE DYNAMIC PROTOTYPE-AWARE NETWORK FOR CROSS-DOMAIN HYPERSPECTRAL IMAGE CHANGE DETECTION
Wenhui Hou, Jiangtao Peng, Hubei University, China; Bing Yang, China Jiliang University, China; Weiwei Sun, Ningbo University, China
WE2.P6.4: GENERATIVE VIRTUAL EXEMPLAR LEARNING FOR LABEL-EFFICIENT SATELLITE IMAGE CHANGE DETECTION
Hichem Sahbi, CNRS Sorbonne University, France
WE2.P6.5: CLIP-Based Content-Aware Change Detection for Bi-Temporal Remote Sensing Imagery
Jintao Chen, Fudan University, China; Bo Peng, Shanghai Ocean University, China; Nianzheng Yuan, Mingmin Chi, Dejing Dou, Fudan University, China; Sicong Liu, Tongji University, China; Jón Atli Benediktsson, University of Iceland, Iceland
Resources
No resources available.