sparsenerf.github.io - SparseNeRF

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Description: Project page for SparseNeRF: Distilling Depth Ranking for Few-shot Novel View Synthesis

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TL;DR: We present SparseNeRF, a simple yet effective method that synthesizes novel views given a few images. SparseNeRF distills robust local depth ranking priors from real-world inaccurate depth observations, such as pre-trained monocular depth estimation models or consumer-level depth sensors.

Neural Radiance Field (NeRF) significantly degrades when only a limited number of views are available. To complement the lack of 3D information, depth-based models, such as DSNeRF and MonoSDF, explicitly assume the availability of accurate depth maps of multiple views. They linearly scale the accurate depth maps as supervision to guide the predicted depth of few-shot NeRFs. However, accurate depth maps are difficult and expensive to capture due to wide-range depth distances in the wild. In this work, we pre

Depth maps are coarse: (a) inconsistent 3D geometry; (b) and (c) time jittering; (d) scale-invariant error. Directly scaling the coarse depth maps to a NeRF leads to inconsistent geometry against the expected depth of the NeRF. Instead of directly supervising a NeRF with coarse depth priors, we relax hard depth constraints and distill robust local depth ranking from the coarse depth maps to a NeRF such that the depth ranking of a NeRF is consistent with that of coarse depth. That is, we supervise a NeRF wit

Links to sparsenerf.github.io (4)

• frozenburning.github.io Zhaoxi Chen
• wanggcong.github.io Guangcong Wang - Homepage
• perf-project.github.io PERF
• open3dvr.github.io Open3DVR