Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient Neural Radiance Fields with Learned Depth-Guided Sampling   This paper aims to reduce the rendering time of generalizable radiance
fields. Some recent works equip neural radiance fields with image encoders and
are able to generalize across scenes, which avoids the per-scene optimization.
However, their rendering process is generally very slow. A major factor is that
they sample lots of points in empty space when inferring radiance fields. In
this paper, we present a hybrid scene representation which combines the best of
implicit radiance fields and explicit depth maps for efficient rendering.
Specifically, we first build the cascade cost volume to efficiently predict the
coarse geometry of the scene. The coarse geometry allows us to sample few
points near the scene surface and significantly improves the rendering speed.
This process is fully differentiable, enabling us to jointly learn the depth
prediction and radiance field networks from only RGB images. Experiments show
that the proposed approach exhibits state-of-the-art performance on the DTU,
Real Forward-facing and NeRF Synthetic datasets, while being at least 50 times
faster than previous generalizable radiance field methods. We also demonstrate
the capability of our method to synthesize free-viewpoint videos of dynamic
human performers in real-time. The code will be available at
https://zju3dv.github.io/enerf/.

22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
33
The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
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The categories of this paper are: solv-int
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The categories of this paper are: stat
19
The categories of this paper are: eess