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 …

Decomposing a scene into its shape, reflectance, and illumination is a challenging but
important problem in computer vision and graphics. This problem is inherently more …

Decomposing a scene into its shape, reflectance and illumination is a fundamental problem
in computer vision and graphics. Neural approaches such as NeRF have achieved …

There are billions of photographs on the Internet, representing an extremely large, rich, and
nearly comprehensive visual record of virtually every famous place on Earth. Unfortunately …

Intrinsic image decomposition separates an image into a reflectance layer and a shading
layer. Automatic intrinsic image decomposition remains a significant challenge, particularly …

The Internet has become an unprecedented source of visual information about our world,
with millions of people uploading photos and videos to media-sharing sites at staggering …

We present a CNN-based technique to estimate high-dynamic range outdoor illumination
from a single low dynamic range image. To train the CNN, we leverage a large dataset of …

We show how to train a fully convolutional neural network to perform inverse rendering from
a single, uncontrolled image. The network takes an RGB image as input, regresses albedo …

Photo-editing software restricts the control of objects in a photograph to the 2D image plane.
We present a method that enables users to perform the full range of 3D manipulations …

We present a study of in-camera image processing through an extensive analysis of more
than 10,000 images from over 30 cameras. The goal of this work is to investigate if image …