1 citations · 1 across the 4 of their papers we have counts for
5 papers
CoToGrasp: Contact-Topology-Conditioned Dexterous Grasp Synthesis via Canonical Workspace Learning
Julien Merand, Boris Meden, Liming Chen +1
Current dexterous grasp planners primarily optimize for physical stability, focusing on whether an object can be grasped rather than how it should be grasped to support downstream…
GOAG: Generative and Object-Agnostic Grasp Planner for Dexterous Robotic Manipulation
Julien Merand, Boris Meden, Mathieu Grossard +1
Multifingered grasping is a crucial robotic skill, but current deep-learning grasp planners often struggle to generalize to new objects because they are trained on limited, object-…
Leveraging CVAE for Joint Configuration Estimation of Multifingered Grippers from Point Cloud Data
Julien Merand, Boris Meden, Mathieu Grossard
This paper presents an efficient approach for determining the joint configuration of a multifingered gripper solely from the point cloud data of its poly-articulated chain, as gene…
Corr2Distrib: Making Ambiguous Correspondences an Ally to Predict Reliable 6D Pose Distributions
Asma Brazi, Boris Meden, Fabrice Mayran de Chamisso +2
We introduce Corr2Distrib, the first correspondence-based method which estimates a 6D camera pose distribution from an RGB image, explaining the observations. Indeed, symmetries an…
BOP-Distrib: Revisiting 6D Pose Estimation Benchmarks for Better Evaluation under Visual Ambiguities
Boris Meden, Asma Brazi, Fabrice Mayran de Chamisso +2
6D pose estimation aims at determining the object pose that best explains the camera observation. The unique solution for non-ambiguous objects can turn into a multi-modal pose dis…