Chenyang Lei (雷晨阳)

Chenyang Lei is a third year Ph.D. student at the Hong Kong University of Science and Technology (HKUST), supervised by Qifeng Chen. He obtained his Bachelor's degree at Zhejiang University in 2018.

Email / CV / Github / Google Scholar / Linked In

News (Mar 2021): Two papers are accepted to CVPR 2021.

Research

I'm interested in Low-level vision, Computational photography, Image and video synthesis, Image and video processing, and 3D vision.

	Deep Video Prior for Video Consistency and Propagation Chenyang Lei, Yazhou Xing, Hao Ouyang, Qifeng Chen In Submission , 2021 code We extend the deep video prior (NeurIPS 2020) to video propagation. We also improve the training efficiency for deep video prior.
	Robust Reflection Removal with Reflection-free Flash-only Cues Chenyang Lei, Qifeng Chen CVPR , 2021 arxiv / code / project website We propose a simple yet effective reflection-free cue for robust reflection removal from a pair of flash and ambient (no-flash) images. The reflection-free cue exploits a flash-only image obtained by subtracting the ambient image from the corresponding flash image in raw data space. The flash-only image is equivalent to an image taken in a dark environment with only a flash on.
	Neural Camera Simulators Hao Ouyang, Zifan Shi, Chenyang Lei, Ka Lung Law, Qifeng Chen CVPR , 2021 paper We present a controllable camera simulator based on deep neural networks to synthesize raw image data under different camera settings, including exposure time, ISO, and aperture.
	Blind Video Temporal Consistency via Deep Video Prior Chenyang Lei, Yazhou Xing, Qifeng Chen NeurIPS , 2020 arxiv / code / project website Applying image processing algorithms independently to each video frame often leads to temporal inconsistency in the resulted video. To address this issue, we present a novel and general approach for blind temporal video consistency.
	Video Depth Estimation by Fusing Flow-to-Depth Proposals Jiaxin Xie, Chenyang Lei, Zhuwen Li, Li Erran Li, Qifeng Chen IROS , 2020 arXiv / code / project website We present an approach with a differentiable flowto-depth layer for video depth estimation.
	Polarized Reflection Removal with Perfect Alignment in the Wild Chenyang Lei, Xuhua Huang, Mengdi Zhang, Qiong Yan, Wenxiu Sun, Qifeng Chen CVPR, 2020 arXiv / code / project website Polarization information and perfect alignment are utilized to remove reflection accurately.
	Fully Automatic Video Colorization with Self Regularization and Diversity Chenyang Lei, Qifeng Chen CVPR, 2019 project page / video / code The first dedicated video colorization method without any user input.