65 citations · 221 across the 23 of their papers we have counts for
8 papers · 1 filter
FINO: Flow-based Joint Image and Noise Model
Lanqing Guo, Siyu Huang, Haosen Liu +1
One of the fundamental challenges in image restoration is denoising, where the objective is to estimate the clean image from its noisy measurements. To tackle such an ill-posed inv…
Cross-Model Consensus of Explanations and Beyond for Image Classification Models: An Empirical Study
Xuhong Li, Haoyi Xiong, Siyu Huang +2
Existing interpretation algorithms have found that, even deep models make the same and right predictions on the same image, they might rely on different sets of input features for…
AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators
Yihang Yin, Qingzhong Wang, Siyu Huang +2
Contrastive learning has been widely applied to graph representation learning, where the view generators play a vital role in generating effective contrastive samples. Most of the…
Semi-Supervised Active Learning with Temporal Output Discrepancy
Siyu Huang, Tianyang Wang, Haoyi Xiong +2
While deep learning succeeds in a wide range of tasks, it highly depends on the massive collection of annotated data which is expensive and time-consuming. To lower the cost of dat…
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…
Practical Assessment of Generalization Performance Robustness for Deep Networks via Contrastive Examples
Xuanyu Wu, Xuhong Li, Haoyi Xiong +3
Training images with data transformations have been suggested as contrastive examples to complement the testing set for generalization performance evaluation of deep neural network…
ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows
Jie An, Siyu Huang, Yibing Song +3
Universal style transfer retains styles from reference images in content images. While existing methods have achieved state-of-the-art style transfer performance, they are not awar…
BM-NAS: Bilevel Multimodal Neural Architecture Search
Yihang Yin, Siyu Huang, Xiang Zhang
Deep neural networks (DNNs) have shown superior performances on various multimodal learning problems. However, it often requires huge efforts to adapt DNNs to individual multimodal…