We address the problem of recovering the shape and spatially-varying reflectance of an
object from multi-view images (and their camera poses) of an object illuminated by one …

Gradient-based methods are becoming increasingly important for computer graphics,
machine learning, and computer vision. The ability to compute gradients is crucial to …

We propose a differentiable sphere tracing algorithm to bridge the gap between inverse
graphics methods and the recently proposed deep learning based implicit signed distance …

A fundamental problem in computer vision is that of inferring the intrinsic, 3D structure of the
world from flat, 2D images of that world. Traditional methods for recovering scene properties …

Reconstructing shape and reflectance properties from images is a highly under-constrained
problem, and has previously been addressed by using specialized hardware to capture …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

We present a method for estimating neural scenes representations of objects given only a
single image. The core of our method is the estimation of a geometric scaffold for the object …

This survey paper discusses the three-dimensional image processing challenges posed by
present and future immersive telecommunications, especially immersive video conferencing …

Like virtual reality, augmented reality is becoming an emerging platform in new application
areas for museums, edutainment, home entertainment, research, industry, and the art …

We present a new approach for modeling and rendering existing architectural scenes from a
sparse set of still photographs. Our modeling approach, which combines both geometry …