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 Jun 2023 • Juan C. Pérez, Sara Rojas, Jesus Zarzar, Bernard Ghanem
We found that introducing image augmentations during training presents challenges such as geometric and photometric inconsistencies for learning NRMs from images.
1 code implementation • ICCV 2023 • Sara Rojas, Jesus Zarzar, Juan Camilo Perez, Artsiom Sanakoyeu, Ali Thabet, Albert Pumarola, Bernard Ghanem
Re-ReND is designed to achieve real-time performance by converting the NeRF into a representation that can be efficiently processed by standard graphics pipelines.
no code implementations • 21 Nov 2022 • Jesus Zarzar, Sara Rojas, Silvio Giancola, Bernard Ghanem
The predicted semantic fields allow SegNeRF to achieve an average mIoU of $\textbf{30. 30%}$ for 2D novel view segmentation, and $\textbf{37. 46%}$ for 3D part segmentation, boasting competitive performance against point-based methods by using only a few posed images.
1 code implementation • ECCV 2020 • Abdullah Hamdi, Sara Rojas, Ali Thabet, Bernard Ghanem
Our proposed attack increases the attack success rate by up to 40% for those transferred to unseen networks (transferability), while maintaining a high success rate on the attacked network.