no code implementations • 5 Apr 2024 • Yang Zheng, Qingqing Zhao, Guandao Yang, Wang Yifan, Donglai Xiang, Florian Dubost, Dmitry Lagun, Thabo Beeler, Federico Tombari, Leonidas Guibas, Gordon Wetzstein
This marks a significant advancement towards modeling photorealistic digital humans using physically based inverse rendering with physics in the loop.
no code implementations • 5 Dec 2023 • Prafull Sharma, Varun Jampani, Yuanzhen Li, Xuhui Jia, Dmitry Lagun, Fredo Durand, William T. Freeman, Mark Matthews
We propose a method to control material attributes of objects like roughness, metallic, albedo, and transparency in real images.
no code implementations • 27 Oct 2023 • Kyle Sargent, Zizhang Li, Tanmay Shah, Charles Herrmann, Hong-Xing Yu, Yunzhi Zhang, Eric Ryan Chan, Dmitry Lagun, Li Fei-Fei, Deqing Sun, Jiajun Wu
Further, we observe that Score Distillation Sampling (SDS) tends to truncate the distribution of complex backgrounds during distillation of 360-degree scenes, and propose "SDS anchoring" to improve the diversity of synthesized novel views.
no code implementations • ICCV 2023 • Marcel C. Bühler, Kripasindhu Sarkar, Tanmay Shah, Gengyan Li, Daoye Wang, Leonhard Helminger, Sergio Orts-Escolano, Dmitry Lagun, Otmar Hilliges, Thabo Beeler, Abhimitra Meka
NeRFs have enabled highly realistic synthesis of human faces including complex appearance and reflectance effects of hair and skin.
1 code implementation • ICCV 2023 • Cheng Zhang, Xuanbai Chen, Siqi Chai, Chen Henry Wu, Dmitry Lagun, Thabo Beeler, Fernando de la Torre
We show that, for some attributes, images can represent concepts more expressively than text.
no code implementations • 24 Mar 2023 • Vishal Vinod, Tanmay Shah, Dmitry Lagun
Our key insight is that by mapping the input image pixels onto the texture space we can achieve near perfect reconstruction (>= 74 dB PSNR at 1024^2 resolution).
no code implementations • 14 Mar 2023 • Axel Levy, Mark Matthews, Matan Sela, Gordon Wetzstein, Dmitry Lagun
Neural radiance fields enable novel-view synthesis and scene reconstruction with photorealistic quality from a few images, but require known and accurate camera poses.
no code implementations • 21 Sep 2022 • Daniel Rebain, Mark J. Matthews, Kwang Moo Yi, Gopal Sharma, Dmitry Lagun, Andrea Tagliasacchi
Neural fields model signals by mapping coordinate inputs to sampled values.
1 code implementation • CVPR 2022 • Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam Laradji, Hsueh-Ti, Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Oztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and training details.
no code implementations • 16 Dec 2021 • Giannis Daras, Wen-Sheng Chu, Abhishek Kumar, Dmitry Lagun, Alexandros G. Dimakis
We introduce a novel framework for solving inverse problems using NeRF-style generative models.
no code implementations • CVPR 2022 • Daniel Rebain, Mark Matthews, Kwang Moo Yi, Dmitry Lagun, Andrea Tagliasacchi
We present a method for learning a generative 3D model based on neural radiance fields, trained solely from data with only single views of each object.
no code implementations • 27 Nov 2017 • Matan Sela, Pingmei Xu, Junfeng He, Vidhya Navalpakkam, Dmitry Lagun
Recent research has demonstrated the ability to estimate gaze on mobile devices by performing inference on the image from the phone's front-facing camera, and without requiring specialized hardware.