120 citations · 175 across the 9 of their papers we have counts for
10 papers
Event Trojan: Asynchronous Event-based Backdoor Attacks
Ruofei Wang, Qing Guo, Haoliang Li +1
As asynchronous event data is more frequently engaged in various vision tasks, the risk of backdoor attacks becomes more evident. However, research into the potential risk associat…
Imaging Interiors: An Implicit Solution to Electromagnetic Inverse Scattering Problems
Ziyuan Luo, Boxin Shi, Haoliang Li +1
Electromagnetic Inverse Scattering Problems (EISP) have gained wide applications in computational imaging. By solving EISP, the internal relative permittivity of the scatterer can…
Temporal Coherent Test-Time Optimization for Robust Video Classification
Chenyu Yi, Siyuan Yang, Yufei Wang +3
Deep neural networks are likely to fail when the test data is corrupted in real-world deployment (e.g., blur, weather, etc.). Test-time optimization is an effective way that adapts…
Benchmarking the Robustness of Spatial-Temporal Models Against Corruptions
Chenyu Yi, Siyuan Yang, Haoliang Li +2
The state-of-the-art deep neural networks are vulnerable to common corruptions (e.g., input data degradations, distortions, and disturbances caused by weather changes, system error…
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…
Low-Light Image Enhancement with Normalizing Flow
Yufei Wang, Renjie Wan, Wenhan Yang +3
To enhance low-light images to normally-exposed ones is highly ill-posed, namely that the mapping relationship between them is one-to-many. Previous works based on the pixel-wise r…
Variational Disentanglement for Domain Generalization
Yufei Wang, Haoliang Li, Hao Cheng +3
Domain generalization aims to learn an invariant model that can generalize well to the unseen target domain. In this paper, we propose to tackle the problem of domain generalizatio…
Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowledge Distillation
Yufei Wang, Haoliang Li, Lap-pui Chau +1
Though convolutional neural networks are widely used in different tasks, lack of generalization capability in the absence of sufficient and representative data is one of the challe…
Heterogeneous Domain Generalization via Domain Mixup
Yufei Wang, Haoliang Li, Alex C. Kot
One of the main drawbacks of deep Convolutional Neural Networks (DCNN) is that they lack generalization capability. In this work, we focus on the problem of heterogeneous domain ge…
Face Image Reflection Removal
Renjie Wan, Boxin Shi, Haoliang Li +2
Face images captured through the glass are usually contaminated by reflections. The non-transmitted reflections make the reflection removal more challenging than for general scenes…