1 citations · 1 across the 4 of their papers we have counts for
4 papers
Flowing With Purpose: Latent Action Guided Flow Matching Policies For Robotic Manipulation
Bruno Machado, Alexandre Chapin, Emmanuel Dellandrea +1
Flow matching has recently become a new standard for behavior cloning in robotic manipulation. However, state-of-the-art flow matching policies suffer from a systematic structural…
XmoPipe: A Pipeline for Large-Scale In-the-Wild Human Motion Dataset Construction
Nathan Salazar, Emmanuel Dellandréa, Mathieu Lefort +1
Large-scale human motion datasets are essential for training robust motion models for analysis, synthesis, and understanding. While marker-based motion capture provides precise dat…
Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss for Better Single-Source Domain Generalization
Thomas Duboudin, Emmanuel Dellandréa, Corentin Abgrall +2
Traditional deep learning algorithms often fail to generalize when they are tested outside of the domain of the training data. The issue can be mitigated by using unlabeled data fr…
Scoring Graspability based on Grasp Regression for Better Grasp Prediction
Amaury Depierre, Emmanuel Dellandréa, Liming Chen
Grasping objects is one of the most important abilities that a robot needs to master in order to interact with its environment. Current state-of-the-art methods rely on deep neural…