1.6k citations · 2.7k across the 11 of their papers we have counts for
12 papers
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…
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary
Yingzhen Yang, Jiahui Yu, Nebojsa Jojic +2
We present a novel method of compression of deep Convolutional Neural Networks (CNNs) by weight sharing through a new representation of convolutional filters. The proposed method r…