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.