5 papers
Toward Deep Representation Learning for Event-Enhanced Visual Autonomous Perception: the eAP Dataset
Jinghang Li, Shichao Li, Qing Lian +3
Recent visual autonomous perception systems achieve remarkable performances with deep representation learning. However, they fail in scenarios with challenging illumination.While e…
EvTTC: An Event Camera Dataset for Time-to-Collision Estimation
Kaizhen Sun, Jinghang Li, Kuan Dai +3
Time-to-Collision (TTC) estimation lies in the core of the forward collision warning (FCW) functionality, which is key to all Automatic Emergency Braking (AEB) systems. Although th…
Event-Aided Time-to-Collision Estimation for Autonomous Driving
Jinghang Li, Bangyan Liao, Xiuyuan LU +3
Predicting a potential collision with leading vehicles is an essential functionality of any autonomous/assisted driving system. One bottleneck of existing vision-based solutions is…
Motion and Structure from Event-based Normal Flow
Zhongyang Ren, Bangyan Liao, Delei Kong +5
Recovering the camera motion and scene geometry from visual data is a fundamental problem in the field of computer vision. Its success in standard vision is attributed to the matur…
BeNeRF: Neural Radiance Fields from a Single Blurry Image and Event Stream
Wenpu Li, Pian Wan, Peng Wang +3
Neural implicit representation of visual scenes has attracted a lot of attention in recent research of computer vision and graphics. Most prior methods focus on how to reconstruct…