activity
20192021
most citedHeterogeneous Domain Generalization via Domain Mixup

120 citations · 156 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2021

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…

eess.IV202133 cited

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…

cs.CV20212 cited

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…

cs.CV2020120 cited

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…

cs.CV20191 cited

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…