no code implementations • 14 May 2022 • Jonathan Tremblay, Moustafa Meshry, Alex Evans, Jan Kautz, Alexander Keller, Sameh Khamis, Thomas Müller, Charles Loop, Nathan Morrical, Koki Nagano, Towaki Takikawa, Stan Birchfield
We present a large-scale synthetic dataset for novel view synthesis consisting of ~300k images rendered from nearly 2000 complex scenes using high-quality ray tracing at high resolution (1600 x 1600 pixels).
Ranked #1 on Novel View Synthesis on RTMV
no code implementations • ICCV 2021 • Moustafa Meshry, Saksham Suri, Larry S. Davis, Abhinav Shrivastava
In contrast, we propose to factorize the representation of a subject into its spatial and style components.
no code implementations • CVPR 2021 • Moustafa Meshry, Yixuan Ren, Larry S Davis, Abhinav Shrivastava
Specifically, we pre-train a generic style encoder using a novel proxy task to learn an embedding of images, from arbitrary domains, into a low-dimensional style latent space.
no code implementations • 25 Sep 2019 • Moustafa Meshry, Yixuan Ren, Ricardo Martin-Brualla, Larry Davis, Abhinav Shrivastava
Then we train a generator to transform an input image along with a style-code to the output domain.
no code implementations • CVPR 2019 • Moustafa Meshry, Dan B. Goldman, Sameh Khamis, Hugues Hoppe, Rohit Pandey, Noah Snavely, Ricardo Martin-Brualla
Starting from internet photos of a tourist landmark, we apply traditional 3D reconstruction to register the photos and approximate the scene as a point cloud.
no code implementations • 16 Jun 2018 • Ahmed Taha, Moustafa Meshry, Xitong Yang, Yi-Ting Chen, Larry Davis
The self-supervised pre-trained weights effectiveness is validated on the action recognition task.
1 code implementation • 23 Dec 2017 • Rohan Chandra, Sachin Grover, Kyungjun Lee, Moustafa Meshry, Ahmed Taha
A novel loss function, FLTBNK, is used for training the texture synthesizer.
no code implementations • 4 Feb 2015 • Moustafa Meshry, Mohamed E. Hussein, Marwan Torki
It identifies the sub-interval with the maximum classifier score in linear time.