My research topics include computer vision, graphics, and neural fields,
specifically in inferring the physical world (shape, appearance, motion, etc.) and camera poses from images.
We recover NeRF from tourism images with variable appearance and occlusions,
consistently rendering free-occlusion views with hallucinated appearances.
We propose a navigation command matching model to discriminate actions generated from sub-optimal policies via smooth rewards.
Projects
Kuafu (Autonomous Vehicle) IEEE Intelligent Transportation Systems Institute Lead Award
Second Place for Navigating in GPS-denied Environments, Intelligent Vehicle Future Challenge, 2019
Lidar Odometry, Mapping, and Localization.
Robotic Hand Xingyu Chen,
Zhili Liu,
Yi Liu,
Yang Li,
Chenyang Liu
National Second Prize, The 11th Chinese College Students Computer Design Contest, 2018
Sensor fusion of IMU and BLE for localization.
Hand gesture recognition based on computer vision.
Robot hand controller based on potentiometer.
Robotic Arm Xingyu Chen,
Zhili Liu,
Yang Li
National Second Prize, The 11th iCAN International Contest of innovAtioN, 2017
Hand gesture recognition based on computer vision.
Structure design based on four-bar linkage.
Invited Talks
光影幻象:神经辐射场中的时空流转 Xingyu Chen Shenlan College online education, 2022
Introduction about Neural Radiance Fields (NeRF) for unconstrained photo collections.
Including NeRF, NeRF in the Wild, and Ha-NeRF