Application of Ghost-DeblurGAN to Fiducial Marker Detection
Yibo Liu,Amaldev Haridevan,Hunter Schofield,Jinjun Shan,Yibo Liu,Amaldev Haridevan,Hunter Schofield,Jinjun Shan
Feature extraction or localization based on the fiducial marker could fail due to motion blur in real-world robotic applications. To solve this problem, a lightweight generative adversarial network, named Ghost-DeblurGAN, for real-time motion deblurring is developed in this paper. Furthermore, on account that there is no existing deblurring benchmark for such task, a new large-scale dataset, York-...
