activity
20172022
most citedCare about you: towards large-scale human-centric visual relationship detection

18 citations · 59 across the 7 of their papers we have counts for

collaborators

17 papers

cs.CV20224 cited

Automated Progressive Learning for Efficient Training of Vision Transformers

Changlin Li, Bohan Zhuang, Guangrun Wang +3

Recent advances in vision Transformers (ViTs) have come with a voracious appetite for computing power, high-lighting the urgent need to develop efficient training methods for ViTs.…

cs.CV2021

Scalable Vision Transformers with Hierarchical Pooling

Zizheng Pan, Bohan Zhuang, Jing Liu +2

The recently proposed Visual image Transformers (ViT) with pure attention have achieved promising performance on image recognition tasks, such as image classification. However, the…

eess.IV20201 cited

Fully Quantized Image Super-Resolution Networks

Hu Wang, Peng Chen, Bohan Zhuang +1

With the rising popularity of intelligent mobile devices, it is of great practical significance to develop accurate, realtime and energy-efficient image Super-Resolution (SR) infer…

cs.LG202018 cited

Role-Wise Data Augmentation for Knowledge Distillation

Jie Fu, Xue Geng, Zhijian Duan +6

Knowledge Distillation (KD) is a common method for transferring the ``knowledge'' learned by one machine learning model (the \textit{teacher}) into another model (the \textit{stude…

cs.CV2020

Generative Low-bitwidth Data Free Quantization

Shoukai Xu, Haokun Li, Bohan Zhuang +4

Neural network quantization is an effective way to compress deep models and improve their execution latency and energy efficiency, so that they can be deployed on mobile or embedde…

cs.CV202016 cited

Switchable Precision Neural Networks

Luis Guerra, Bohan Zhuang, Ian Reid +1

Instantaneous and on demand accuracy-efficiency trade-off has been recently explored in the context of neural networks slimming. In this paper, we propose a flexible quantization s…