419 citations · 777 across the 33 of their papers we have counts for
10 papers · 1 filter
AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results
Dario Fuoli, Zhiwu Huang, Shuhang Gu +23
This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR)…
Video Super-Resolution with Recurrent Structure-Detail Network
Takashi Isobe, Xu Jia, Shuhang Gu +3
Most video super-resolution methods super-resolve a single reference frame with the help of neighboring frames in a temporal sliding window. They are less efficient compared to the…
You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network
Boyun Li, Yuanbiao Gou, Shuhang Gu +3
In this paper, we study two challenging and less-touched problems in single image dehazing, namely, how to make deep learning achieve image dehazing without training on the ground-…
The Heterogeneity Hypothesis: Finding Layer-Wise Differentiated Network Architectures
Yawei Li, Wen Li, Martin Danelljan +4
In this paper, we tackle the problem of convolutional neural network design. Instead of focusing on the design of the overall architecture, we investigate a design space that is us…
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte +60
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input im…
Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network
Dario Kneubuehler, Shuhang Gu, Luc Van Gool +1
We propose the first practical multitask image enhancement network, that is able to learn one-to-many and many-to-one image mappings. We show that our model outperforms the current…
Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning
Kangning Liu, Shuhang Gu, Andres Romero +1
Existing unsupervised video-to-video translation methods fail to produce translated videos which are frame-wise realistic, semantic information preserving and video-level consisten…
Unsupervised Real-world Image Super Resolution via Domain-distance Aware Training
Yunxuan Wei, Shuhang Gu, Yawei Li +1
These days, unsupervised super-resolution (SR) has been soaring due to its practical and promising potential in real scenarios. The philosophy of off-the-shelf approaches lies in t…
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression
Yawei Li, Shuhang Gu, Christoph Mayer +2
In this paper, we analyze two popular network compression techniques, i.e. filter pruning and low-rank decomposition, in a unified sense. By simply changing the way the sparsity re…
DHP: Differentiable Meta Pruning via HyperNetworks
Yawei Li, Shuhang Gu, Kai Zhang +2
Network pruning has been the driving force for the acceleration of neural networks and the alleviation of model storage/transmission burden. With the advent of AutoML and neural ar…