A Novel Spike Transformer Network for Depth Estimation from Event Cameras via Cross-modality Knowledge Distillation

arXiv:2404.17335v1 Announce Type: new
Abstract: Depth estimation is crucial for interpreting complex environments, especially in areas such as autonomous vehicle navigation and robotics. Nonetheless, obtaining accurate depth readings from event camera data remains a formidable challenge. Event cameras operate differently from traditional digital cameras, continuously capturing data and generating asynchronous binary spikes that encode time, location, and light intensity. Yet, the unique sampling mechanisms of event cameras render standard image based algorithms inadequate for processing spike data. This necessitates the …

abstract arxiv autonomous autonomous vehicle cameras challenge cs.ai cs.cv data digital distillation environments event knowledge navigation network novel robotics transformer transformer network type via