832 citations · 1.7k across the 27 of their papers we have counts for
7 papers · 1 filter
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…
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…
DiffTaichi: Differentiable Programming for Physical Simulation
Yuanming Hu, Luke Anderson, Tzu-Mao Li +4
We present DiffTaichi, a new differentiable programming language tailored for building high-performance differentiable physical simulators. Based on an imperative programming langu…
Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions
Guha Balakrishnan, Adrian V. Dalca, Amy Zhao +3
We introduce visual deprojection: the task of recovering an image or video that has been collapsed along a dimension. Projections arise in various contexts, such as long-exposure p…
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)…
Data augmentation using learned transformations for one-shot medical image segmentation
Amy Zhao, Guha Balakrishnan, Frédo Durand +2
Image segmentation is an important task in many medical applications. Methods based on convolutional neural networks attain state-of-the-art accuracy; however, they typically rely…