1 code implementation • 29 Apr 2024 • Guillaume Astruc, Nicolas Dufour, Ioannis Siglidis, Constantin Aronssohn, Nacim Bouia, Stephanie Fu, Romain Loiseau, Van Nguyen Nguyen, Charles Raude, Elliot Vincent, Lintao XU, HongYu Zhou, Loic Landrieu
Determining the location of an image anywhere on Earth is a complex visual task, which makes it particularly relevant for evaluating computer vision algorithms.
Ranked #1 on Photo geolocation estimation on OpenStreetView-5M
no code implementations • 14 Mar 2024 • Tomas Hodan, Martin Sundermeyer, Yann Labbe, Van Nguyen Nguyen, Gu Wang, Eric Brachmann, Bertram Drost, Vincent Lepetit, Carsten Rother, Jiri Matas
In the new tasks, methods were required to learn new objects during a short onboarding stage (max 5 minutes, 1 GPU) from provided 3D object models.
1 code implementation • 23 Nov 2023 • Van Nguyen Nguyen, Thibault Groueix, Mathieu Salzmann, Vincent Lepetit
We present GigaPose, a fast, robust, and accurate method for CAD-based novel object pose estimation in RGB images.
1 code implementation • 20 Jul 2023 • Van Nguyen Nguyen, Thibault Groueix, Georgy Ponimatkin, Vincent Lepetit, Tomas Hodan
We propose a simple three-stage approach to segment unseen objects in RGB images using their CAD models.
1 code implementation • 23 Mar 2023 • Van Nguyen Nguyen, Thibault Groueix, Yinlin Hu, Mathieu Salzmann, Vincent Lepetit
The practicality of 3D object pose estimation remains limited for many applications due to the need for prior knowledge of a 3D model and a training period for new objects.
1 code implementation • 15 Sep 2022 • Van Nguyen Nguyen, Yuming Du, Yang Xiao, Michael Ramamonjisoa, Vincent Lepetit
Our results on challenging datasets are on par with previous works that require much more information (training images of the target objects, 3D models, and/or depth data).
2 code implementations • CVPR 2022 • Van Nguyen Nguyen, Yinlin Hu, Yang Xiao, Mathieu Salzmann, Vincent Lepetit
It relies on a small set of training objects to learn local object representations, which allow us to locally match the input image to a set of "templates", rendered images of the CAD models for the new objects.