"In this paper, we introduce a practical approach that enables mixing colors with K–M while keeping everything in RGB. We achieve this by establishing a latent color space, where RGB colors are represented as mixtures of primary pigments together with additive residuals. The latents can be manipulated with linear operations, leading to expected, plausible results."

Inspired by how motion-capture systems use a set of point markers to estimate full bone rotations, this method uses virtual markers to generate sufficient information to accurately infer rotations with simple post processing.

Using the uncoupled limited Laval HDR lighting dataset and the larger 3D60 color and normal dataset jointly, coupling them through relighting in order to learn a single-shot HDR lighting estimator from a single LDR spherical panorama.

FILM turns near-duplicate photos into a slow motion footage that look like shot with a video camera.

A small neural network is augmented by a multiresolution hash table of trainable feature vectors whose values are optimized through stochastic gradient descent. The multiresolution structure allows the network to disambiguate hash collisions, making for a simple architecture that is trivial to parallelize on modern GPUs.

Presents an extension of mip-NeRF (a NeRF variant that addresses sampling and aliasing) that uses a non-linear scene parameterization, online distillation, and a novel distortion-based regularizer to overcome the challenges presented by unbounded scenes.

Presents an efficient method for joint optimization of topology, materials and lighting from multi-view image observations