43 citations · 113 across the 17 of their papers we have counts for
16 papers · 1 filter
Making Your First Choice: To Address Cold Start Problem in Vision Active Learning
Liangyu Chen, Yutong Bai, Siyu Huang +4
Active learning promises to improve annotation efficiency by iteratively selecting the most important data to be annotated first. However, we uncover a striking contradiction to th…
Adversarial Purification through Representation Disentanglement
Tao Bai, Jun Zhao, Lanqing Guo +1
Deep learning models are vulnerable to adversarial examples and make incomprehensible mistakes, which puts a threat on their real-world deployment. Combined with the idea of advers…
Disentangled Feature Representation for Few-shot Image Classification
Hao Cheng, Yufei Wang, Haoliang Li +2
Learning the generalizable feature representation is critical for few-shot image classification. While recent works exploited task-specific feature embedding using meta-tasks for f…
ReLLIE: Deep Reinforcement Learning for Customized Low-Light Image Enhancement
Rongkai Zhang, Lanqing Guo, Siyu Huang +1
Low-light image enhancement (LLIE) is a pervasive yet challenging problem, since: 1) low-light measurements may vary due to different imaging conditions in practice; 2) images can…
Reconciliation of Statistical and Spatial Sparsity For Robust Image and Image-Set Classification
Hao Cheng, Kim-Hui Yap, Bihan Wen
Recent image classification algorithms, by learning deep features from large-scale datasets, have achieved significantly better results comparing to the classic feature-based appro…
Systematic Analysis and Removal of Circular Artifacts for StyleGAN
Way Tan, Bihan Wen, Xulei Yang
StyleGAN is one of the state-of-the-art image generators which is well-known for synthesizing high-resolution and hyper-realistic face images. Though images generated by vanilla St…