no code implementations • 7 Dec 2022 • Siddhant Ranade, Christoph Lassner, Kai Li, Christian Haene, Shen-Chi Chen, Jean-Charles Bazin, Sofien Bouaziz
Neural Radiance Fields (NeRFs) encode the radiance in a scene parameterized by the scene's plenoptic function.
no code implementations • ICCV 2021 • Zhang Chen, yinda zhang, Kyle Genova, Sean Fanello, Sofien Bouaziz, Christian Haene, Ruofei Du, Cem Keskin, Thomas Funkhouser, Danhang Tang
To the best of our knowledge, MDIF is the first deep implicit function model that can at the same time (1) represent different levels of detail and allow progressive decoding; (2) support both encoder-decoder inference and decoder-only latent optimization, and fulfill multiple applications; (3) perform detailed decoder-only shape completion.
2 code implementations • 24 Jun 2021 • Keunhong Park, Utkarsh Sinha, Peter Hedman, Jonathan T. Barron, Sofien Bouaziz, Dan B Goldman, Ricardo Martin-Brualla, Steven M. Seitz
A common approach to reconstruct such non-rigid scenes is through the use of a learned deformation field mapping from coordinates in each input image into a canonical template coordinate space.
1 code implementation • CVPR 2021 • Feitong Tan, Danhang Tang, Mingsong Dou, Kaiwen Guo, Rohit Pandey, Cem Keskin, Ruofei Du, Deqing Sun, Sofien Bouaziz, Sean Fanello, Ping Tan, yinda zhang
In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses.
no code implementations • 22 Mar 2021 • Shlok Kumar Mishra, Kuntal Sengupta, Max Horowitz-Gelb, Wen-Sheng Chu, Sofien Bouaziz, David Jacobs
Presentation attack detection (PAD) is a critical component in secure face authentication.
1 code implementation • ICCV 2021 • Keunhong Park, Utkarsh Sinha, Jonathan T. Barron, Sofien Bouaziz, Dan B Goldman, Steven M. Seitz, Ricardo Martin-Brualla
We present the first method capable of photorealistically reconstructing deformable scenes using photos/videos captured casually from mobile phones.
no code implementations • ECCV 2020 • Ricardo Martin-Brualla, Rohit Pandey, Sofien Bouaziz, Matthew Brown, Dan B. Goldman
Accurate modeling of 3D objects exhibiting transparency, reflections and thin structures is an extremely challenging problem.
8 code implementations • CVPR 2021 • Vladimir Tankovich, Christian Häne, yinda zhang, Adarsh Kowdle, Sean Fanello, Sofien Bouaziz
Contrary to many recent neural network approaches that operate on a full cost volume and rely on 3D convolutions, our approach does not explicitly build a volume and instead relies on a fast multi-resolution initialization step, differentiable 2D geometric propagation and warping mechanisms to infer disparity hypotheses.
Ranked #1 on Stereo Depth Estimation on KITTI2015
no code implementations • CVPR 2020 • Danhang Tang, Saurabh Singh, Philip A. Chou, Christian Haene, Mingsong Dou, Sean Fanello, Jonathan Taylor, Philip Davidson, Onur G. Guleryuz, yinda zhang, Shahram Izadi, Andrea Tagliasacchi, Sofien Bouaziz, Cem Keskin
We describe a novel approach for compressing truncated signed distance fields (TSDF) stored in 3D voxel grids, and their corresponding textures.
no code implementations • 10 Feb 2020 • Hossam Isack, Christian Haene, Cem Keskin, Sofien Bouaziz, Yuri Boykov, Shahram Izadi, Sameh Khamis
At the coarsest resolution, and in a manner similar to classical part-based approaches, we leverage the kinematic structure of the human body to propagate convolutional feature updates between the keypoints or body parts.
no code implementations • CVPR 2020 • Boyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz, Geoffrey Hinton, Andrea Tagliasacchi
We introduce a network architecture to represent a low dimensional family of convexes.
1 code implementation • NeurIPS 2019 • Srinath Sridhar, Davis Rempe, Julien Valentin, Sofien Bouaziz, Leonidas J. Guibas
We investigate the problem of learning category-specific 3D shape reconstruction from a variable number of RGB views of previously unobserved object instances.
no code implementations • 25 Apr 2016 • Tiantian Liu, Sofien Bouaziz, Ladislav Kavan
In this paper, we show that Projective Dynamics can be interpreted as a quasi-Newton method.
no code implementations • EPFL 2015 • Alexandru Eugen Ichim, Sofien Bouaziz, Mark Pauly, EPFL
From this user- and expression-specific data, we learn a regressor for on-the-fly detail synthesis during animation to enhance the perceptual realism of the avatars.