Publications (10)
Minibatch Processing in Spiking Neural Networks
Daniel J. Saunders, Cooper Sigrist, Kenneth Chaney +2
Spiking neural networks (SNNs) are a promising candidate for biologically-inspired and energy efficient computation. However, their simulation is notoriously time consuming, and ma…
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks
Chankyu Lee, Adarsh Kumar Kosta, Alex Zihao Zhu +3
Event-based cameras display great potential for a variety of tasks such as high-speed motion detection and navigation in low-light environments where conventional frame-based camer…
Event-based Continuous Color Video Decompression from Single Frames
Ziyun Wang, Friedhelm Hamann, Kenneth Chaney +3
We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional cameras struggle with high-speed m…
Motion-prior Contrast Maximization for Dense Continuous-Time Motion Estimation
Friedhelm Hamann, Ziyun Wang, Ioannis Asmanis +3
Current optical flow and point-tracking methods rely heavily on synthetic datasets. Event cameras are novel vision sensors with advantages in challenging visual conditions, but sta…
EvAC3D: From Event-based Apparent Contours to 3D Models via Continuous Visual Hulls
Ziyun Wang, Kenneth Chaney, Kostas Daniilidis
3D reconstruction from multiple views is a successful computer vision field with multiple deployments in applications. State of the art is based on traditional RGB frames that enab…
EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras
Alex Zihao Zhu, Liangzhe Yuan, Kenneth Chaney +1
Event-based cameras have shown great promise in a variety of situations where frame based cameras suffer, such as high speed motions and high dynamic range scenes. However, develop…