153 citations · 158 across the 7 of their papers we have counts for
9 papers
HAMSt3R: Human-Aware Multi-view Stereo 3D Reconstruction
Sara Rojas, Matthieu Armando, Bernard Ghamen +3
Recovering the 3D geometry of a scene from a sparse set of uncalibrated images is a long-standing problem in computer vision. While recent learning-based approaches such as DUSt3R…
UnMix-NeRF: Spectral Unmixing Meets Neural Radiance Fields
Fabian Perez, Sara Rojas, Carlos Hinojosa +2
Neural Radiance Field (NeRF)-based segmentation methods focus on object semantics and rely solely on RGB data, lacking intrinsic material properties. This limitation restricts accu…
Deep Learning at the Intersection: Certified Robustness as a Tool for 3D Vision
Gabriel Pérez S, Juan C. Pérez, Motasem Alfarra +4
This paper presents preliminary work on a novel connection between certified robustness in machine learning and the modeling of 3D objects. We highlight an intriguing link between…
TrackNeRF: Bundle Adjusting NeRF from Sparse and Noisy Views via Feature Tracks
Jinjie Mai, Wenxuan Zhu, Sara Rojas +6
Neural radiance fields (NeRFs) generally require many images with accurate poses for accurate novel view synthesis, which does not reflect realistic setups where views can be spars…
DATENeRF: Depth-Aware Text-based Editing of NeRFs
Sara Rojas, Julien Philip, Kai Zhang +4
Recent advancements in diffusion models have shown remarkable proficiency in editing 2D images based on text prompts. However, extending these techniques to edit scenes in Neural R…
Enhancing Neural Rendering Methods with Image Augmentations
Juan C. Pérez, Sara Rojas, Jesus Zarzar +1
Faithfully reconstructing 3D geometry and generating novel views of scenes are critical tasks in 3D computer vision. Despite the widespread use of image augmentations across comput…
Re-ReND: Real-time Rendering of NeRFs across Devices
Sara Rojas, Jesus Zarzar, Juan Camilo Perez +4
This paper proposes a novel approach for rendering a pre-trained Neural Radiance Field (NeRF) in real-time on resource-constrained devices. We introduce Re-ReND, a method enabling…
SegNeRF: 3D Part Segmentation with Neural Radiance Fields
Jesus Zarzar, Sara Rojas, Silvio Giancola +1
Recent advances in Neural Radiance Fields (NeRF) boast impressive performances for generative tasks such as novel view synthesis and 3D reconstruction. Methods based on neural radi…
AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds
Abdullah Hamdi, Sara Rojas, Ali Thabet +1
Deep neural networks are vulnerable to adversarial attacks, in which imperceptible perturbations to their input lead to erroneous network predictions. This phenomenon has been exte…