105 citations · 332 across the 15 of their papers we have counts for
15 papers
Low-Light Image Enhancement by Learning Contrastive Representations in Spatial and Frequency Domains
Yi Huang, Xiaoguang Tu, Gui Fu +4
Images taken under low-light conditions tend to suffer from poor visibility, which can decrease image quality and even reduce the performance of the downstream tasks. It is hard fo…
Image-to-Video Generation via 3D Facial Dynamics
Xiaoguang Tu, Yingtian Zou, Jian Zhao +8
We present a versatile model, FaceAnime, for various video generation tasks from still images. Video generation from a single face image is an interesting problem and usually tackl…
Joint Face Image Restoration and Frontalization for Recognition
Xiaoguang Tu, Jian Zhao, Qiankun Liu +5
In real-world scenarios, many factors may harm face recognition performance, e.g., large pose, bad illumination,low resolution, blur and noise. To address these challenges, previou…
Single Image Super-Resolution via Residual Neuron Attention Networks
Wenjie Ai, Xiaoguang Tu, Shilei Cheng +1
Deep Convolutional Neural Networks (DCNNs) have achieved impressive performance in Single Image Super-Resolution (SISR). To further improve the performance, existing CNN-based meth…
What's the relationship between CNNs and communication systems?
Hao Ge, Xiaoguang Tu, Yanxiang Gong +2
The interpretability of Convolutional Neural Networks (CNNs) is an important topic in the field of computer vision. In recent years, works in this field generally adopt a mature mo…
Face Attribute Invertion
X G Tu, Y Luo, H S Zhang +3
Manipulating human facial images between two domains is an important and interesting problem. Most of the existing methods address this issue by applying two generators or one gene…