14 citations · 34 across the 12 of their papers we have counts for
12 papers
Understanding Spatio-Temporal Relations in Human-Object Interaction using Pyramid Graph Convolutional Network
Hao Xing, Darius Burschka
Human activities recognition is an important task for an intelligent robot, especially in the field of human-robot collaboration, it requires not only the label of sub-activities b…
Speeding Up Optimization-based Motion Planning through Deep Learning
Johannes Tenhumberg, Darius Burschka, Berthold Bäuml
Planning collision-free motions for robots with many degrees of freedom is challenging in environments with complex obstacle geometries. Recent work introduced the idea of speeding…
Self-Contained Calibration of an Elastic Humanoid Upper Body Using Only a Head-Mounted RGB Camera
Johannes Tenhumberg, Dominik Winkelbauer, Darius Burschka +1
When a humanoid robot performs a manipulation task, it first makes a model of the world using its visual sensors and then plans the motion of its body in this model. For this, prec…
Joint Prediction of Monocular Depth and Structure using Planar and Parallax Geometry
Hao Xing, Yifan Cao, Maximilian Biber +2
Supervised learning depth estimation methods can achieve good performance when trained on high-quality ground-truth, like LiDAR data. However, LiDAR can only generate sparse 3D map…
Skeletal Human Action Recognition using Hybrid Attention based Graph Convolutional Network
Hao Xing, Darius Burschka
In skeleton-based action recognition, Graph Convolutional Networks model human skeletal joints as vertices and connect them through an adjacency matrix, which can be seen as a loca…
Robust Event Detection based on Spatio-Temporal Latent Action Unit using Skeletal Information
Hao Xing, Yuxuan Xue, Mingchuan Zhou +1
This paper propose a novel dictionary learning approach to detect event action using skeletal information extracted from RGBD video. The event action is represented as several late…