160 citations · 425 across the 18 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.CV2020★ 2 cited
AQD: Towards Accurate Fully-Quantized Object Detection
Peng Chen, Jing Liu, Bohan Zhuang +2
Network quantization allows inference to be conducted using low-precision arithmetic for improved inference efficiency of deep neural networks on edge devices. However, designing a…
cs.CV2020★ 14 cited
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.CV2020★ 154 cited
Discrimination-aware Network Pruning for Deep Model Compression
Jing Liu, Bohan Zhuang, Zhuangwei Zhuang +4
We study network pruning which aims to remove redundant channels/kernels and hence speed up the inference of deep networks. Existing pruning methods either train from scratch with…