133 citations · 147 across the 11 of their papers we have counts for
6 papers · 1 filter
Video Frame Interpolation Transformer
Zhihao Shi, Xiangyu Xu, Xiaohong Liu +2
Existing methods for video interpolation heavily rely on deep convolution neural networks, and thus suffer from their intrinsic limitations, such as content-agnostic kernel weights…
Towards a Unified Approach to Single Image Deraining and Dehazing
Xiaohong Liu, Yongrui Ma, Zhihao Shi +2
We develop a new physical model for the rain effect and show that the well-known atmosphere scattering model (ASM) for the haze effect naturally emerges as its homogeneous continuo…
GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task Knowledge Transfer for Single Image Dehazing
Xiaohong Liu, Zhihao Shi, Zijun Wu +1
We propose an enhanced multi-scale network, dubbed GridDehazeNet+, for single image dehazing. The proposed dehazing method does not rely on the Atmosphere Scattering Model (ASM), a…
Learning for Unconstrained Space-Time Video Super-Resolution
Zhihao Shi, Xiaohong Liu, Chengqi Li +4
Recent years have seen considerable research activities devoted to video enhancement that simultaneously increases temporal frame rate and spatial resolution. However, the existing…
Video Frame Interpolation via Generalized Deformable Convolution
Zhihao Shi, Xiaohong Liu, Kangdi Shi +2
Video frame interpolation aims at synthesizing intermediate frames from nearby source frames while maintaining spatial and temporal consistencies. The existing deep-learning-based…
GridDehazeNet: Attention-Based Multi-Scale Network for Image Dehazing
Xiaohong Liu, Yongrui Ma, Zhihao Shi +1
We propose an end-to-end trainable Convolutional Neural Network (CNN), named GridDehazeNet, for single image dehazing. The GridDehazeNet consists of three modules: pre-processing,…