We present a comprehensive study and evaluation of existing single image low-light enhancement algorithms from the perspective of both human perception and machine vision. Beyond the traditional evaluations in the view of low-level vision, we make the first attempt to set and address a novel task, i.e. face detection in the low-light condition, to explore the potential of benefiting high-level vision tasks with image enhancement methods, both off-line and in an end-to-end manner.
Based on the observation that various objects and backgrounds have different material, reflection and perspective attributes, regions of a single low-light image may require different adjustment and enhancement regarding contrast, illumination and noise. We propose an enhancement pipeline with three parts which effectively utilize the semantic layer information. Specifically, we extract the segmentation layer as well as the reflectance, and illumination, and concurrently enhance every separate region, i.g. sky, ground and objects for outdoor scenes.
GPA: 3.55/4.00 (Overall)
I developed a bot using greedy algorithm for the game of Ataxx on Botzone in the course 'Introduction to Computation'.
This project includes a simulation program of a WeChat game : ‘The Strongest Projectile’. Also, we wrote a DQN algorithm which taught the agent to play the game. (Ref: https://github.com/RuntianZ/IRL)
A simple file server which enables users to manage their files as well as setup groups with friends for file sharing. (Ref: https://github.com/XFW-go/PKU-Web-Project)