HyperE2VID: Improving Event-Based Video Reconstruction via Hypernetworks

arXiv:2305.06382v2 Announce Type: replace
Abstract: Event-based cameras are becoming increasingly popular for their ability to capture high-speed motion with low latency and high dynamic range. However, generating videos from events remains challenging due to the highly sparse and varying nature of event data. To address this, in this study, we propose HyperE2VID, a dynamic neural network architecture for event-based video reconstruction. Our approach uses hypernetworks to generate per-pixel adaptive filters guided by a context fusion module that combines information from …

abstract arxiv cameras cs.cv data dynamic event events latency low low latency nature popular speed study type via video videos