activity
20182023
most citedAdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices

10 citations · 15 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20232 cited

Localised Adaptive Spatial-Temporal Graph Neural Network

Wenying Duan, Xiaoxi He, Zimu Zhou +2

Spatial-temporal graph models are prevailing for abstracting and modelling spatial and temporal dependencies. In this work, we ask the following question: whether and to what exten…

cs.CV202210 cited

AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices

Sicong Liu, Xiaochen Li, Zimu Zhou +4

The ubiquity of camera-embedded devices and the advances in deep learning have stimulated various intelligent mobile video applications. These applications often demand on-device p…

cs.LG20203 cited

AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles

Sicong Liu, Junzhao Du, Kaiming Nan +3

Recent breakthroughs in Deep Neural Networks (DNNs) have fueled a tremendously growing demand for bringing DNN-powered intelligence into mobile platforms. While the potential of de…

cs.CV2019

Adaptive Loss-aware Quantization for Multi-bit Networks

Zhongnan Qu, Zimu Zhou, Yun Cheng +1

We investigate the compression of deep neural networks by quantizing their weights and activations into multiple binary bases, known as multi-bit networks (MBNs), which accelerate…

cs.NE2018

Multi-Task Zipping via Layer-wise Neuron Sharing

Xiaoxi He, Zimu Zhou, Lothar Thiele

Future mobile devices are anticipated to perceive, understand and react to the world on their own by running multiple correlated deep neural networks on-device. Yet the complexity…