The fidelity of relighting is bounded by both geometry and appearance representations. For
geometry both mesh and volumetric approaches have difficulty modeling intricate structures …

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 …

We present a method that takes as input a set of images of a scene illuminated by
unconstrained known lighting, and produces as output a 3D representation that can be …

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 …

Very recently neural implicit rendering techniques have been rapidly evolved and shown
great advantages in novel view synthesis and 3D scene reconstruction. However, existing …

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 …

In this paper, we focus on the problem of rendering novel views from a Neural Radiance
Field (NeRF) under unobserved light conditions. To this end, we introduce a novel dataset …

This paper presents a novel neural implicit radiance representation for free viewpoint
relighting from a small set of unstructured photographs of an object lit by a moving point light …

Recovering the physical attributes of an object's appearance from its images captured under
an unknown illumination is challenging yet essential for photo-realistic rendering. Recent …

This paper presents a novel method for exerting fine-grained lighting control during text-
driven diffusion-based image generation. While existing diffusion models already have the …