activity
20172022
most citedShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

892 citations · 1.6k across the 7 of their papers we have counts for

collaborators

14 papers

cs.CV20206 cited

Rethinking Learnable Tree Filter for Generic Feature Transform

Lin Song, Yanwei Li, Zhengkai Jiang +5

The Learnable Tree Filter presents a remarkable approach to model structure-preserving relations for semantic segmentation. Nevertheless, the intrinsic geometric constraint forces…

stat.ML2020

Spherical Motion Dynamics: Learning Dynamics of Neural Network with Normalization, Weight Decay, and SGD

Ruosi Wan, Zhanxing Zhu, Xiangyu Zhang +1

In this work, we comprehensively reveal the learning dynamics of neural network with normalization, weight decay (WD), and SGD (with momentum), named as Spherical Motion Dynamics (…

cs.CV201944 cited

Meta-SR: A Magnification-Arbitrary Network for Super-Resolution

Xuecai Hu, Haoyuan Mu, Xiangyu Zhang +3

Recent research on super-resolution has achieved great success due to the development of deep convolutional neural networks (DCNNs). However, super-resolution of arbitrary scale fa…

cs.CV2019

Single Path One-Shot Neural Architecture Search with Uniform Sampling

Zichao Guo, Xiangyu Zhang, Haoyuan Mu +4

We revisit the one-shot Neural Architecture Search (NAS) paradigm and analyze its advantages over existing NAS approaches. Existing one-shot method, however, is hard to train and n…

cs.CV2019

MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning

Zechun Liu, Haoyuan Mu, Xiangyu Zhang +4

In this paper, we propose a novel meta learning approach for automatic channel pruning of very deep neural networks. We first train a PruningNet, a kind of meta network, which is a…

cs.CV2018

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng +1

Currently, the neural network architecture design is mostly guided by the \emph{indirect} metric of computation complexity, i.e., FLOPs. However, the \emph{direct} metric, e.g., sp…