PFRL: Pose-Free Reinforcement Learning for 6D Pose Estimation

CVPR 2020 Jianzhun Shao Yuhang Jiang Gu Wang Zhigang Li Xiangyang Ji

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-world ground-truth 6D object poses, whose collection is fairly cumbersome and expensive, even unavailable in many cases... (read more)

PDF Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.