100 citations · 249 across the 12 of their papers we have counts for
3 papers · 1 filter
PFRL: Pose-Free Reinforcement Learning for 6D Pose Estimation
Jianzhun Shao, Yuhang Jiang, Gu Wang +2
6D pose estimation from a single RGB image is a challenging and vital task in computer vision. The current mainstream deep model methods resort to 2D images annotated with real-wor…
GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimator
Xingyu Liu, Ruida Zhang, Chenyangguang Zhang +4
6D pose estimation of rigid objects is a long-standing and challenging task in computer vision. Recently, the emergence of deep learning reveals the potential of Convolutional Neur…
Robust RGB-based 6-DoF Pose Estimation without Real Pose Annotations
Zhigang Li, Yinlin Hu, Mathieu Salzmann +1
While much progress has been made in 6-DoF object pose estimation from a single RGB image, the current leading approaches heavily rely on real-annotation data. As such, they remain…