SEARCH PUBLICATIONS

This paper proposes a novel architecture combining an asynchronous accumulation-free event branch and a periodic aggregation branch to break the accuracy-latency trade-off. The solution enables ultra low-latency and low-power optical flow prediction from event cameras, achieving per-event prediction with a latency of tens of microseconds.

The paper evaluates Prophesee’s 3rd-generation event-based cameras for space domain awareness, showing potential for efficient, low-power temporal sensing despite sensitivity limits.

In this paper, the traditional techniques of conventional astronomy are reconsidered to properly utilise the event-based camera for space imaging and space situational awareness.

This paper addresses these challenges by introducing a novel motion segmentation method that leverages self-supervised vision transformers on both event data and optical flow information. Our approach eliminates the need for human annotations and reduces dependency on scene-specific parameters.

This paper introduces hybrid coaxial event-frame devices to build the multimodal system, and propose a coaxial stereo event camera (CoSEC) dataset for autonomous driving. As for the multimodal system, it first utilizes the microcontroller to achieve time synchronization, and then spatially calibrate different sensors, where they perform intra- and inter-calibration of stereo coaxial devices.

This paper presents Ev-Layout, a novel large-scale event-based multi-modal dataset designed for indoor layout estimation and tracking. Ev-Layout makes key contributions to the community by: Utilizing a hybrid data collection platform (with a head-mounted display and VR interface) that integrates both RGB and bio-inspired event cameras to capture indoor layouts in motion.