883 citations · 1.1k across the 30 of their papers we have counts for
6 papers · 1 filter
Face Deblurring Based on Separable Normalization and Adaptive Denormalization
Xian Zhang, Hao Zhang, Jiancheng Lv +1
Face deblurring aims to restore a clear face image from a blurred input image with more explicit structure and facial details. However, most conventional image and face deblurring…
Dynamic Normalization
Chuan Liu, Yi Gao, Jiancheng Lv
Batch Normalization has become one of the essential components in CNN. It allows the network to use a higher learning rate and speed up training. And the network doesn't need to be…
Learning Event-Based Motion Deblurring
Zhe Jiang, Yu Zhang, Dongqing Zou +3
Recovering sharp video sequence from a motion-blurred image is highly ill-posed due to the significant loss of motion information in the blurring process. For event-based cameras,…
Domain Embedded Multi-model Generative Adversarial Networks for Image-based Face Inpainting
Xian Zhang, Xin Wang, Bin Kong +6
Prior knowledge of face shape and structure plays an important role in face inpainting. However, traditional face inpainting methods mainly focus on the generated image resolution…
Deep Density-aware Count Regressor
Zhuojun Chen, Junhao Cheng, Yuchen Yuan +3
We seek to improve crowd counting as we perceive limits of currently prevalent density map estimation approach on both prediction accuracy and time efficiency. We leverage multilev…
Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine
Dongdong Chen, Jiancheng Lv, Mike E. Davies
We investigate the potential of a restricted Boltzmann Machine (RBM) for discriminative representation learning. By imposing the class information preservation constraints on the h…