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

Estimating the surface reflectance properties of a spatially-varying material is a challenging
problem. Methods based on inverse rendering (eg,[Dong et al. 2014; Hui et al. 2017]) can …

Inverse rendering aims to estimate physical attributes of a scene, eg, reflectance, geometry,
and lighting, from image (s). Inverse rendering has been studied primarily for single objects …

We present a neural rendering-based method called NeRO for reconstructing the geometry
and the BRDF of reflective objects from multiview images captured in an unknown …

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 …

Recent advances in implicit neural representations and differentiable rendering make it
possible to simultaneously recover the geometry and materials of an object from multi-view …

We address the problem of reconstructing spatially-varying BRDFs from a small set of image
measurements. This is a fundamentally under-constrained problem, and previous work has …

Inverse rendering methods aim to estimate geometry, materials and illumination from multi-
view RGB images. In order to achieve better decomposition, recent approaches attempt to …

Reconstructing the shape and appearance of real‐world objects using measured 2D images
has been a long‐standing inverse rendering problem. In this paper, we introduce a new …

We present an end-to-end inverse rendering pipeline that includes a fully differentiable
renderer, and can reconstruct geometry, materials, and illumination from scratch from a set …