235 citations · 412 across the 5 of their papers we have counts for
9 papers · 1 filter
Neural Sparse Representation for Image Restoration
Yuchen Fan, Jiahui Yu, Yiqun Mei +4
Inspired by the robustness and efficiency of sparse representation in sparse coding based image restoration models, we investigate the sparsity of neurons in deep networks. Our met…
Pyramid Attention Networks for Image Restoration
Yiqun Mei, Yuchen Fan, Yulun Zhang +6
Self-similarity refers to the image prior widely used in image restoration algorithms that small but similar patterns tend to occur at different locations and scales. However, rece…
Scale-wise Convolution for Image Restoration
Yuchen Fan, Jiahui Yu, Ding Liu +1
While scale-invariant modeling has substantially boosted the performance of visual recognition tasks, it remains largely under-explored in deep networks based image restoration. Na…
AutoSlim: Towards One-Shot Architecture Search for Channel Numbers
Jiahui Yu, Thomas Huang
We study how to set channel numbers in a neural network to achieve better accuracy under constrained resources (e.g., FLOPs, latency, memory footprint or model size). A simple and…
Universally Slimmable Networks and Improved Training Techniques
Jiahui Yu, Thomas Huang
Slimmable networks are a family of neural networks that can instantly adjust the runtime width. The width can be chosen from a predefined widths set to adaptively optimize accuracy…
Foreground-aware Image Inpainting
Wei Xiong, Jiahui Yu, Zhe Lin +4
Existing image inpainting methods typically fill holes by borrowing information from surrounding pixels. They often produce unsatisfactory results when the holes overlap with or to…