Original paper
Neural volumes: learning dynamic renderable volumes from images
Abstract
Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain complex phenomena such as thin structures, evolving topology, translucency, scattering, occlusion, and biological motion. Mesh-based reconstruction and tracking often fail in these cases, and other approaches (e.g., light field video) typically rely on constrained viewing conditions, which limit interactivity. We circumvent these difficulties by presenting a...
Paper Details
Title
Neural volumes: learning dynamic renderable volumes from images
Published Date
Jul 12, 2019
Journal
Volume
38
Issue
4
Pages
65
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