4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 1 cited
Consolidator: Mergeable Adapter with Grouped Connections for Visual Adaptation
Tianxiang Hao, Hui Chen, Yuchen Guo +1
Recently, transformers have shown strong ability as visual feature extractors, surpassing traditional convolution-based models in various scenarios. However, the success of vision…
cs.CV2021★ 4 cited
Manipulating Identical Filter Redundancy for Efficient Pruning on Deep and Complicated CNN
Xiaohan Ding, Tianxiang Hao, Jungong Han +2
The existence of redundancy in Convolutional Neural Networks (CNNs) enables us to remove some filters/channels with acceptable performance drops. However, the training objective of…
cs.LG2020
ResRep: Lossless CNN Pruning via Decoupling Remembering and Forgetting
Xiaohan Ding, Tianxiang Hao, Jianchao Tan +4
We propose ResRep, a novel method for lossless channel pruning (a.k.a. filter pruning), which slims down a CNN by reducing the width (number of output channels) of convolutional la…