activity
20172019
most citedApproximated Oracle Filter Pruning for Destructive CNN Width Optimization

46 citations · 119 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV201930 cited

Aggregation Signature for Small Object Tracking

Chunlei Liu, Wenrui Ding, Jinyu Yang +4

Small object tracking becomes an increasingly important task, which however has been largely unexplored in computer vision. The great challenges stem from the facts that: 1) small…

cs.CV2019

ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks

Xiaohan Ding, Yuchen Guo, Guiguang Ding +1

As designing appropriate Convolutional Neural Network (CNN) architecture in the context of a given application usually involves heavy human works or numerous GPU hours, the researc…

cs.LG201946 cited

Approximated Oracle Filter Pruning for Destructive CNN Width Optimization

Xiaohan Ding, Guiguang Ding, Yuchen Guo +2

It is not easy to design and run Convolutional Neural Networks (CNNs) due to: 1) finding the optimal number of filters (i.e., the width) at each layer is tricky, given an architect…

cs.LG201914 cited

Centripetal SGD for Pruning Very Deep Convolutional Networks with Complicated Structure

Xiaohan Ding, Guiguang Ding, Yuchen Guo +1

The redundancy is widely recognized in Convolutional Neural Networks (CNNs), which enables to remove unimportant filters from convolutional layers so as to slim the network with ac…

cs.CV2019

Pixelated Semantic Colorization

Jiaojiao Zhao, Jungong Han, Ling Shao +1

While many image colorization algorithms have recently shown the capability of producing plausible color versions from gray-scale photographs, they still suffer from limited semant…

cs.CV201818 cited

Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation

Jiaxin Gu, Ce Li, Baochang Zhang +4

The advancement of deep convolutional neural networks (DCNNs) has driven significant improvement in the accuracy of recognition systems for many computer vision tasks. However, the…