Zobrazeno 1 - 10
of 500
pro vyhledávání: '"Lepetit, Vincent"'
Online object segmentation and tracking in Lidar point clouds enables autonomous agents to understand their surroundings and make safe decisions. Unfortunately, manual annotations for these tasks are prohibitively costly. We tackle this problem with
Externí odkaz:
http://arxiv.org/abs/2409.07887
Autor:
Cafaro, Alexandre, Leroy, Amaury, Beldjoudi, Guillaume, Maury, Pauline, Robert, Charlotte, Deutsch, Eric, Grégoire, Vincent, Lepetit, Vincent, Paragios, Nikos
We introduce a novel unsupervised approach to reconstructing a 3D volume from only two planar projections that exploits a previous\-ly-captured 3D volume of the patient. Such volume is readily available in many important medical procedures and previo
Externí odkaz:
http://arxiv.org/abs/2405.11977
We propose PyTorchGeoNodes, a differentiable module for reconstructing 3D objects from images using interpretable shape programs. In comparison to traditional CAD model retrieval methods, the use of shape programs for 3D reconstruction allows for rea
Externí odkaz:
http://arxiv.org/abs/2404.10620
Autor:
Guédon, Antoine, Lepetit, Vincent
We propose Gaussian Frosting, a novel mesh-based representation for high-quality rendering and editing of complex 3D effects in real-time. Our approach builds on the recent 3D Gaussian Splatting framework, which optimizes a set of 3D Gaussians to app
Externí odkaz:
http://arxiv.org/abs/2403.14554
Autor:
Hodan, Tomas, Sundermeyer, Martin, Labbe, Yann, Nguyen, Van Nguyen, Wang, Gu, Brachmann, Eric, Drost, Bertram, Lepetit, Vincent, Rother, Carsten, Matas, Jiri
We present the evaluation methodology, datasets and results of the BOP Challenge 2023, the fifth in a series of public competitions organized to capture the state of the art in model-based 6D object pose estimation from an RGB/RGB-D image and related
Externí odkaz:
http://arxiv.org/abs/2403.09799
Computer vision has long relied on two kinds of correspondences: pixel correspondences in images and 3D correspondences on object surfaces. Is there another kind, and if there is, what can they do for us? In this paper, we introduce correspondences o
Externí odkaz:
http://arxiv.org/abs/2312.04527
We present GigaPose, a fast, robust, and accurate method for CAD-based novel object pose estimation in RGB images. GigaPose first leverages discriminative "templates", rendered images of the CAD models, to recover the out-of-plane rotation and then u
Externí odkaz:
http://arxiv.org/abs/2311.14155
Autor:
Guédon, Antoine, Lepetit, Vincent
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 rendering while being significantly faster to train than NeRFs. It is howev
Externí odkaz:
http://arxiv.org/abs/2311.12775
We present a surprisingly simple and efficient method for self-supervision of 3D backbone on automotive Lidar point clouds. We design a contrastive loss between features of Lidar scans captured in the same scene. Several such approaches have been pro
Externí odkaz:
http://arxiv.org/abs/2310.17281
We present an automated and efficient approach for retrieving high-quality CAD models of objects and their poses in a scene captured by a moving RGB-D camera. We first investigate various objective functions to measure similarity between a candidate
Externí odkaz:
http://arxiv.org/abs/2309.06107