Non‐rigid registration computes an alignment between a source surface with a target surface in a non‐rigid manner. In the past decade, with the advances in 3D sensing …
H Wang, X Du, J Li, RA Yeh… - Proceedings of the …, 2023 - openaccess.thecvf.com
A diffusion model learns to predict a vector field of gradients. We propose to apply chain rule on the learned gradients, and back-propagate the score of a diffusion model through the …
Neural Radiance Fields (NeRF) are a rapidly growing area of research with wide-ranging applications in computer vision, graphics, robotics, and more. In order to streamline the …
Neural surface reconstruction has been shown to be powerful for recovering dense 3D surfaces via image-based neural rendering. However, current methods struggle to recover …
In recent years, neural implicit surface reconstruction methods have become popular for multi-view 3D reconstruction. In contrast to traditional multi-view stereo methods, these …
Diffusion models have emerged as the state-of-the-art for image generation, among other tasks. Here, we present an efficient diffusion-based model for 3D-aware generation of neural …
We present TensoRF, a novel approach to model and reconstruct radiance fields. Unlike NeRF that purely uses MLPs, we model the radiance field of a scene as a 4D tensor, which …
A Guédon, V Lepetit - … of the IEEE/CVF Conference on …, 2024 - openaccess.thecvf.com
We propose a method to allow precise and extremely fast mesh extraction from 3D Gaussian Splatting. Gaussian Splatting has recently become very popular as it yields realistic …
T Wu, J Zhang, X Fu, Y Wang, J Ren… - Proceedings of the …, 2023 - openaccess.thecvf.com
Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of large-scale real-scanned 3D databases. To facilitate the development of 3D perception …