We propose an analysis-by-synthesis method for fast multi-view 3D reconstruction of
opaque objects with arbitrary materials and illumination. State-of-the-art methods use both
neural surface representations and neural rendering. While flexible, neural surface
representations are a significant bottleneck in optimization runtime. Instead, we represent
surfaces as triangle meshes and build a differentiable rendering pipeline around triangle
rasterization and neural shading. The renderer is used in a gradient descent optimization …

With publicly available code, means for mitigation would be difficult to implement from our
side. However, we feel that the overall potential for misuse is low and there are few obvious
paths to malicious use or potential damage. Also, our method requires a set of calibrated
images, thus is much less accessible than 3D reconstruction or deep fakes based on single
images.