2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2022
MixFormer: Mixing Features across Windows and Dimensions
Qiang Chen, Qiman Wu, Jian Wang +5
While local-window self-attention performs notably in vision tasks, it suffers from limited receptive field and weak modeling capability issues. This is mainly because it performs…
cs.CV2021★ 2 cited
Joint Channel and Weight Pruning for Model Acceleration on Moblie Devices
Tianli Zhao, Xi Sheryl Zhang, Wentao Zhu +4
For practical deep neural network design on mobile devices, it is essential to consider the constraints incurred by the computational resources and the inference latency in various…
cs.CV2021
Architecture Aware Latency Constrained Sparse Neural Networks
Tianli Zhao, Qinghao Hu, Xiangyu He +4
Acceleration of deep neural networks to meet a specific latency constraint is essential for their deployment on mobile devices. In this paper, we design an architecture aware laten…