activity
20172020
most citedLearning Human-Robot Collaboration Insights through the Integration of Muscle Activity in Interaction Motion Models

10 citations · 25 across the 4 of their papers we have counts for

collaborators

11 papers

cs.RO2020

Hyperparameter Auto-tuning in Self-Supervised Robotic Learning

Jiancong Huang, Juan Rojas, Matthieu Zimmer +3

Policy optimization in reinforcement learning requires the selection of numerous hyperparameters across different environments. Fixing them incorrectly may negatively impact optimi…

cs.CV20209 cited

Pose-based Modular Network for Human-Object Interaction Detection

Zhijun Liang, Junfa Liu, Yisheng Guan +1

Human-object interaction(HOI) detection is a critical task in scene understanding. The goal is to infer the triplet <subject, predicate, object> in a scene. In this work, we note t…

cs.CV2020

A Graph Attention Spatio-temporal Convolutional Network for 3D Human Pose Estimation in Video

Junfa Liu, Juan Rojas, Zhijun Liang +2

Spatio-temporal information is key to resolve occlusion and depth ambiguity in 3D pose estimation. Previous methods have focused on either temporal contexts or local-to-global arch…

cs.LG2020

Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection

Zhijun Liang, Juan Rojas, Junfa Liu +1

In scene understanding, robotics benefit from not only detecting individual scene instances but also from learning their possible interactions. Human-Object Interaction (HOI) Detec…

cs.AI20193 cited

Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation

Yijiong Lin, Jiancong Huang, Matthieu Zimmer +2

Deep reinforcement learning (DRL) is a promising approach for adaptive robot control, but its current application to robotics is currently hindered by high sample requirements. We…

cs.RO2019

Invariant Transform Experience Replay: Data Augmentation for Deep Reinforcement Learning

Yijiong Lin, Jiancong Huang, Matthieu Zimmer +3

Deep Reinforcement Learning (RL) is a promising approach for adaptive robot control, but its current application to robotics is currently hindered by high sample requirements. To a…