43 citations · 83 across the 7 of their papers we have counts for
7 papers · 1 filter
Deep scene-scale material estimation from multi-view indoor captures
Siddhant Prakash, Gilles Rainer, Adrien Bousseau +1
The movie and video game industries have adopted photogrammetry as a way to create digital 3D assets from multiple photographs of a real-world scene. But photogrammetry algorithms…
Active Exploration for Neural Global Illumination of Variable Scenes
Stavros Diolatzis, Julien Philip, George Drettakis
Neural rendering algorithms introduce a fundamentally new approach for photorealistic rendering, typically by learning a neural representation of illumination on large numbers of g…
FreeStyleGAN: Free-view Editable Portrait Rendering with the Camera Manifold
Thomas Leimkühler, George Drettakis
Current Generative Adversarial Networks (GANs) produce photorealistic renderings of portrait images. Embedding real images into the latent space of such models enables high-level i…
Free-viewpoint Indoor Neural Relighting from Multi-view Stereo
Julien Philip, Sébastien Morgenthaler, Michaël Gharbi +1
We introduce a neural relighting algorithm for captured indoors scenes, that allows interactive free-viewpoint navigation. Our method allows illumination to be changed syntheticall…
Guided Fine-Tuning for Large-Scale Material Transfer
Valentin Deschaintre, George Drettakis, Adrien Bousseau
We present a method to transfer the appearance of one or a few exemplar SVBRDFs to a target image representing similar materials. Our solution is extremely simple: we fine-tune a d…
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…