211 citations · 402 across the 9 of their papers we have counts for
9 papers
Re-evaluating Parallel Finger-tip Tactile Sensing for Inferring Object Adjectives: An Empirical Study
Fangyi Zhang, Peter Corke
Finger-tip tactile sensors are increasingly used for robotic sensing to establish stable grasps and to infer object properties. Promising performance has been shown in a number of…
Learning Fabric Manipulation in the Real World with Human Videos
Robert Lee, Jad Abou-Chakra, Fangyi Zhang +1
Fabric manipulation is a long-standing challenge in robotics due to the enormous state space and complex dynamics. Learning approaches stand out as promising for this domain as the…
Tracking the Untrackable
Fangyi Zhang
Although short-term fully occlusion happens rare in visual object tracking, most trackers will fail under these circumstances. However, humans can still catch up the target by anti…
SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks
Bo Li, Wei Wu, Qiang Wang +3
Siamese network based trackers formulate tracking as convolutional feature cross-correlation between target template and searching region. However, Siamese trackers still have accu…
Adversarial Discriminative Sim-to-real Transfer of Visuo-motor Policies
Fangyi Zhang, Jürgen Leitner, Zongyuan Ge +2
Various approaches have been proposed to learn visuo-motor policies for real-world robotic applications. One solution is first learning in simulation then transferring to the real…
Tuning Modular Networks with Weighted Losses for Hand-Eye Coordination
Fangyi Zhang, Jürgen Leitner, Michael Milford +1
This paper introduces an end-to-end fine-tuning method to improve hand-eye coordination in modular deep visuo-motor policies (modular networks) where each module is trained indepen…
Modular Deep Q Networks for Sim-to-real Transfer of Visuo-motor Policies
Fangyi Zhang, Jürgen Leitner, Michael Milford +1
While deep learning has had significant successes in computer vision thanks to the abundance of visual data, collecting sufficiently large real-world datasets for robot learning ca…
The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Research
Jürgen Leitner, Adam W. Tow, Jake E. Dean +15
Robotic challenges like the Amazon Picking Challenge (APC) or the DARPA Challenges are an established and important way to drive scientific progress. They make research comparable…
Towards Vision-Based Deep Reinforcement Learning for Robotic Motion Control
Fangyi Zhang, Jürgen Leitner, Michael Milford +2
This paper introduces a machine learning based system for controlling a robotic manipulator with visual perception only. The capability to autonomously learn robot controllers sole…