Sensing Surface Patches in Volume Rendering for Inferring Signed Distance Functions
Journal:
arXiv
Published Date:
Dec 21, 2024
Abstract
It is vital to recover 3D geometry from multi-view RGB images in many 3D
computer vision tasks. The latest methods infer the geometry represented as a
signed distance field by minimizing the rendering error on the field through
volume rendering. However, it is still challenging to explicitly impose
constraints on surfaces for inferring more geometry details due to the limited
ability of sensing surfaces in volume rendering. To resolve this problem, we
introduce a method to infer signed distance functions (SDFs) with a better
sense of surfaces through volume rendering. Using the gradients and signed
distances, we establish a small surface patch centered at the estimated
intersection along a ray by pulling points randomly sampled nearby. Hence, we
are able to explicitly impose surface constraints on the sensed surface patch,
such as multi-view photo consistency and supervision from depth or normal
priors, through volume rendering. We evaluate our method by numerical and
visual comparisons on scene benchmarks. Our superiority over the latest methods
justifies our effectiveness.
