DyBluRF: Dynamic Neural Radiance Fields from Blurry Monocular Video

arXiv:2403.10103v1 Announce Type: new
Abstract: Recent advancements in dynamic neural radiance field methods have yielded remarkable outcomes. However, these approaches rely on the assumption of sharp input images. When faced with motion blur, existing dynamic NeRF methods often struggle to generate high-quality novel views. In this paper, we propose DyBluRF, a dynamic radiance field approach that synthesizes sharp novel views from a monocular video affected by motion blur. To account for motion blur in input images, we simultaneously capture the …

abstract arxiv cs.cv dynamic fields generate however images nerf neural radiance field neural radiance fields novel paper quality struggle type video