26 citations · 40 across the 2 of their papers we have counts for
6 papers
Appearance-Driven Automatic 3D Model Simplification
Jon Hasselgren, Jacob Munkberg, Jaakko Lehtinen +2
We present a suite of techniques for jointly optimizing triangle meshes and shading models to match the appearance of reference scenes. This capability has a number of uses, includ…
Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization
Miika Aittala, Prafull Sharma, Lukas Murmann +4
We recover a video of the motion taking place in a hidden scene by observing changes in indirect illumination in a nearby uncalibrated visible region. We solve this problem by fact…
Analyzing and Improving the Image Quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala +3
The style-based GAN architecture (StyleGAN) yields state-of-the-art results in data-driven unconditional generative image modeling. We expose and analyze several of its characteris…
A Dataset of Multi-Illumination Images in the Wild
Lukas Murmann, Michael Gharbi, Miika Aittala +1
Collections of images under a single, uncontrolled illumination have enabled the rapid advancement of core computer vision tasks like classification, detection, and segmentation. B…
Flexible SVBRDF Capture with a Multi-Image Deep Network
Valentin Deschaintre, Miika Aittala, Fredo Durand +2
Empowered by deep learning, recent methods for material capture can estimate a spatially-varying reflectance from a single photograph. Such lightweight capture is in stark contrast…
Generating Training Data for Denoising Real RGB Images via Camera Pipeline Simulation
Ronnachai Jaroensri, Camille Biscarrat, Miika Aittala +1
Image reconstruction techniques such as denoising often need to be applied to the RGB output of cameras and cellphones. Unfortunately, the commonly used additive white noise (AWGN)…