21 citations · 66 across the 17 of their papers we have counts for
23 papers
Scene-level Tracking and Reconstruction without Object Priors
Haonan Chang, Abdeslam Boularias
We present the first real-time system capable of tracking and reconstructing, individually, every visible object in a given scene, without any form of prior on the rigidness of the…
Learning Category-Level Manipulation Tasks from Point Clouds with Dynamic Graph CNNs
Junchi Liang, Abdeslam Boularias
This paper presents a new technique for learning category-level manipulation from raw RGB-D videos of task demonstrations, with no manual labels or annotations. Category-level lear…
Interleaving Monte Carlo Tree Search and Self-Supervised Learning for Object Retrieval in Clutter
Baichuan Huang, Teng Guo, Abdeslam Boularias +1
In this study, working with the task of object retrieval in clutter, we have developed a robot learning framework in which Monte Carlo Tree Search (MCTS) is first applied to enable…
Learning Sensorimotor Primitives of Sequential Manipulation Tasks from Visual Demonstrations
Junchi Liang, Bowen Wen, Kostas Bekris +1
This work aims to learn how to perform complex robot manipulation tasks that are composed of several, consecutively executed low-level sub-tasks, given as input a few visual demons…
A Self-supervised Learning System for Object Detection in Videos Using Random Walks on Graphs
Juntao Tan, Changkyu Song, Abdeslam Boularias
This paper presents a new self-supervised system for learning to detect novel and previously unseen categories of objects in images. The proposed system receives as input several u…
DIPN: Deep Interaction Prediction Network with Application to Clutter Removal
Baichuan Huang, Shuai D. Han, Abdeslam Boularias +1
We propose a Deep Interaction Prediction Network (DIPN) for learning to predict complex interactions that ensue as a robot end-effector pushes multiple objects, whose physical prop…