63 citations · 139 across the 6 of their papers we have counts for
7 papers
Non-Local Spatial Propagation Network for Depth Completion
Jinsun Park, Kyungdon Joo, Zhe Hu +2
In this paper, we propose a robust and efficient end-to-end non-local spatial propagation network for depth completion. The proposed network takes RGB and sparse depth images as in…
Multi-Scale Boosted Dehazing Network with Dense Feature Fusion
Hang Dong, Jinshan Pan, Lei Xiang +4
In this paper, we propose a Multi-Scale Boosted Dehazing Network with Dense Feature Fusion based on the U-Net architecture. The proposed method is designed based on two principles,…
Gated Fusion Network for Degraded Image Super Resolution
Xinyi Zhang, Hang Dong, Zhe Hu +3
Single image super resolution aims to enhance image quality with respect to spatial content, which is a fundamental task in computer vision. In this work, we address the task of si…
Efficient Super Resolution Using Binarized Neural Network
Yinglan Ma, Hongyu Xiong, Zhe Hu +1
Deep convolutional neural networks (DCNNs) have recently demonstrated high-quality results in single-image super-resolution (SR). DCNNs often suffer from over-parametrization and l…
Gated Fusion Network for Joint Image Deblurring and Super-Resolution
Xinyi Zhang, Hang Dong, Zhe Hu +3
Single-image super-resolution is a fundamental task for vision applications to enhance the image quality with respect to spatial resolution. If the input image contains degraded pi…
Learning to Deblur Images with Exemplars
Jinshan Pan, Wenqi Ren, Zhe Hu +1
Human faces are one interesting object class with numerous applications. While significant progress has been made in the generic deblurring problem, existing methods are less effec…
Multi-Scale Video Frame-Synthesis Network with Transitive Consistency Loss
Zhe Hu, Yinglan Ma, Lizhuang Ma
Traditional approaches to interpolate/extrapolate frames in a video sequence require accurate pixel correspondences between images, e.g., using optical flow. Their results stem on…