6 citations · 10 across the 4 of their papers we have counts for
4 papers
Dyn-Adapter: Towards Disentangled Representation for Efficient Visual Recognition
Yurong Zhang, Honghao Chen, Xinyu Zhang +2
Parameter-efficient transfer learning (PETL) is a promising task, aiming to adapt the large-scale pre-trained model to downstream tasks with a relatively modest cost. However, curr…
Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness
Honghao Chen, Yurong Zhang, Xiaokun Feng +2
Robustness is a vital aspect to consider when deploying deep learning models into the wild. Numerous studies have been dedicated to the study of the robustness of vision transforme…
PeLK: Parameter-efficient Large Kernel ConvNets with Peripheral Convolution
Honghao Chen, Xiangxiang Chu, Yongjian Ren +2
Recently, some large kernel convnets strike back with appealing performance and efficiency. However, given the square complexity of convolution, scaling up kernels can bring about…
RepMLPNet: Hierarchical Vision MLP with Re-parameterized Locality
Xiaohan Ding, Honghao Chen, Xiangyu Zhang +2
Compared to convolutional layers, fully-connected (FC) layers are better at modeling the long-range dependencies but worse at capturing the local patterns, hence usually less favor…