no code implementations • 24 Aug 2023 • Georgios Kopanas, George Drettakis
Neural Radiance Fields, or NeRFs, have drastically improved novel view synthesis and 3D reconstruction for rendering.
1 code implementation • 8 Aug 2023 • Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George Drettakis
Radiance Field methods have recently revolutionized novel-view synthesis of scenes captured with multiple photos or videos.
no code implementations • 3 Jan 2023 • Georgios Kopanas, Thomas Leimkühler, Gilles Rainer, Clément Jambon, George Drettakis
View-dependent effects such as reflections pose a substantial challenge for image-based and neural rendering algorithms.
no code implementations • 15 Nov 2022 • Siddhant Prakash, Gilles Rainer, Adrien Bousseau, George Drettakis
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.
no code implementations • 20 Sep 2021 • Thomas Leimkühler, George Drettakis
In our solution, we use a few images of a face to perform 3D reconstruction, and we introduce the notion of the GAN camera manifold, the key element allowing us to precisely define the range of images that the GAN can reproduce in a stable manner.
no code implementations • 6 Sep 2021 • Georgios Kopanas, Julien Philip, Thomas Leimkühler, George Drettakis
There has recently been great interest in neural rendering methods.
no code implementations • 24 Jun 2021 • Julien Philip, Sébastien Morgenthaler, Michaël Gharbi, George Drettakis
We design a convolutional network around input feature maps that facilitate learning of an implicit representation of scene materials and illumination, enabling both relighting and free-viewpoint navigation.
1 code implementation • 6 Jul 2020 • Valentin Deschaintre, George Drettakis, Adrien Bousseau
Our solution is extremely simple: we fine-tune a deep appearance-capture network on the provided exemplars, such that it learns to extract similar SVBRDF values from the target image.
1 code implementation • 27 Jun 2019 • Valentin Deschaintre, Miika Aittala, Fredo Durand, George Drettakis, Adrien Bousseau
Empowered by deep learning, recent methods for material capture can estimate a spatially-varying reflectance from a single photograph.
Graphics I.3
1 code implementation • SIGGRAPH Asia 2018 2018 • Peter Hedman, Julien Philip, True Price, Jan-Michael Frahm, George Drettakis, Gabriel Brostow
We present a new deep learning approach to blending for IBR, in which we use held-out real image data to learn blending weights to combine input photo contributions.
1 code implementation • 23 Oct 2018 • Valentin Deschaintre, Miika Aittala, Fredo Durand, George Drettakis, Adrien Bousseau
Texture, highlights, and shading are some of many visual cues that allow humans to perceive material appearance in single pictures.
Graphics I.3