73 citations · 133 across the 10 of their papers we have counts for
11 papers
Robotic Manipulation via Imitation Learning: Taxonomy, Evolution, Benchmark, and Challenges
Zezeng Li, Alexandre Chapin, Enda Xiang +6
Robotic Manipulation (RM) is central to the advancement of autonomous robots, enabling them to interact with and manipulate objects in real-world environments. This survey focuses…
Is an object-centric representation beneficial for robotic manipulation ?
Alexandre Chapin, Emmanuel Dellandrea, Liming Chen
Object-centric representation (OCR) has recently become a subject of interest in the computer vision community for learning a structured representation of images and videos. It has…
Object-Centric Representations Improve Policy Generalization in Robot Manipulation
Alexandre Chapin, Bruno Machado, Emmanuel Dellandrea +1
Visual representations are central to the learning and generalization capabilities of robotic manipulation policies. While existing methods rely on global or dense features, such r…
Look Beyond Bias with Entropic Adversarial Data Augmentation
Thomas Duboudin, Emmanuel Dellandréa, Corentin Abgrall +2
Deep neural networks do not discriminate between spurious and causal patterns, and will only learn the most predictive ones while ignoring the others. This shortcut learning behavi…
panda-gym: Open-source goal-conditioned environments for robotic learning
Quentin Gallouédec, Nicolas Cazin, Emmanuel Dellandréa +1
This paper presents panda-gym, a set of Reinforcement Learning (RL) environments for the Franka Emika Panda robot integrated with OpenAI Gym. Five tasks are included: reach, push,…
Bayesian Optimization for Developmental Robotics with Meta-Learning by Parameters Bounds Reduction
Maxime Petit, Emmanuel Dellandrea, Liming Chen
In robotics, methods and softwares usually require optimizations of hyperparameters in order to be efficient for specific tasks, for instance industrial bin-picking from homogeneou…
Deep Multicameral Decoding for Localizing Unoccluded Object Instances from a Single RGB Image
Matthieu Grard, Emmanuel Dellandréa, Liming Chen
Occlusion-aware instance-sensitive segmentation is a complex task generally split into region-based segmentations, by approximating instances as their bounding box. We address the…
Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning
Maxime Petit, Amaury Depierre, Xiaofang Wang +2
We present a developmental framework based on a long-term memory and reasoning mechanisms (Vision Similarity and Bayesian Optimisation). This architecture allows a robot to optimiz…
Jacquard: A Large Scale Dataset for Robotic Grasp Detection
Amaury Depierre, Emmanuel Dellandréa, Liming Chen
Grasping skill is a major ability that a wide number of real-life applications require for robotisation. State-of-the-art robotic grasping methods perform prediction of object gras…
Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection
Yuxing Tang, Josiah Wang, Xiaofang Wang +4
Deep CNN-based object detection systems have achieved remarkable success on several large-scale object detection benchmarks. However, training such detectors requires a large numbe…
Object segmentation in depth maps with one user click and a synthetically trained fully convolutional network
Matthieu Grard, Romain Brégier, Florian Sella +2
With more and more household objects built on planned obsolescence and consumed by a fast-growing population, hazardous waste recycling has become a critical challenge. Given the l…