Zobrazeno 1 - 10
of 4 693
pro vyhledávání: '"A. Lepetit"'
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
Currently, 6D pose estimation methods are benchmarked on datasets that consider, for their ground truth annotations, visual ambiguities as only related to global object symmetries. However, as previously observed [26], visual ambiguities can also hap
Externí odkaz:
http://arxiv.org/abs/2408.17297
Estimating treatment effects over time holds significance in various domains, including precision medicine, epidemiology, economy, and marketing. This paper introduces a unique approach to counterfactual regression over time, emphasizing long-term pr
Externí odkaz:
http://arxiv.org/abs/2406.00535
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
Autor:
Lepetit-Aimon, Gabriel, Playout, Clément, Boucher, Marie Carole, Duval, Renaud, Brent, Michael H, Cheriet, Farida
Publikováno v:
Sci Data 11, 914 (2024)
Reliable automatic diagnosis of Diabetic Retinopathy (DR) and Macular Edema (ME) is an invaluable asset in improving the rate of monitored patients among at-risk populations and in enabling earlier treatments before the pathology progresses and threa
Externí odkaz:
http://arxiv.org/abs/2402.04258
Autor:
Guer, Matthieu, Luttmann, Martin, Hergott, Jean-François, Lepetit, Fabien, Ruchon, Olivier Tcherbakoff Thierry, Géneaux, Romain
We report on the generation of optical vortices with few-cycle pulse durations, 500$\mu$J per pulse, at a repetition rate of 1 kHz. To do so, a 25 fs laser beam at 800 nm is shaped with a helical phase and coupled into a hollow core fiber filled with
Externí odkaz:
http://arxiv.org/abs/2312.11087
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