ActiveNeRF: Learning where to See with Uncertainty Estimation. (arXiv:2209.08546v1 [cs.CV])

Recently, Neural Radiance Fields (NeRF) has shown promising performances on
reconstructing 3D scenes and synthesizing novel views from a sparse set of 2D
images. Albeit effective, the performance of NeRF is highly influenced by the
quality of training samples. With limited posed images from the scene, NeRF
fails to generalize well to novel views and may collapse to trivial solutions
in unobserved regions. This makes NeRF impractical under resource-constrained
scenarios. In this paper, we present a novel learning framework, ActiveNeRF, …

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