no code implementations • 6 Apr 2024 • Sara Rojas, Julien Philip, Kai Zhang, Sai Bi, Fujun Luan, Bernard Ghanem, Kalyan Sunkavall
However, extending these techniques to edit scenes in Neural Radiance Fields (NeRF) is complex, as editing individual 2D frames can result in inconsistencies across multiple views.
no code implementations • 15 Mar 2024 • Peter Kocsis, Julien Philip, Kalyan Sunkavalli, Matthias Nießner, Yannick Hold-Geoffroy
Our method is the first that enables the generation of images with controllable, consistent lighting and performs on par with specialized relighting state-of-the-art methods.
no code implementations • 22 May 2023 • Prafull Sharma, Julien Philip, Michaël Gharbi, William T. Freeman, Fredo Durand, Valentin Deschaintre
We present a method capable of selecting the regions of a photograph exhibiting the same material as an artist-chosen area.
no code implementations • 18 May 2023 • Viraj Shah, Svetlana Lazebnik, Julien Philip
In this work, we propose to solve ill-posed inverse imaging problems using a bank of Generative Adversarial Networks (GAN) as a prior and apply our method to the case of Intrinsic Image Decomposition for faces and materials.
1 code implementation • 4 May 2023 • Julien Philip, Valentin Deschaintre
NeRF acquisition typically requires careful choice of near planes for the different cameras or suffers from background collapse, creating floating artifacts on the edges of the captured scene.
no code implementations • CVPR 2023 • Yichen Sheng, Jianming Zhang, Julien Philip, Yannick Hold-Geoffroy, Xin Sun, He Zhang, Lu Ling, Bedrich Benes
To compensate for the lack of geometry in 2D Image compositing, recent deep learning-based approaches introduced a pixel height representation to generate soft shadows and reflections.
no code implementations • 20 Apr 2022 • David Griffiths, Tobias Ritschel, Julien Philip
We propose a relighting method for outdoor images.
1 code implementation • CVPR 2022 • Qiangeng Xu, Zexiang Xu, Julien Philip, Sai Bi, Zhixin Shu, Kalyan Sunkavalli, Ulrich Neumann
Point-NeRF combines the advantages of these two approaches by using neural 3D point clouds, with associated neural features, to model a radiance field.
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 • 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.