Uni6Dv2: Noise Elimination for 6D Pose Estimation

@article{Sun2022Uni6Dv2NE,
  title={Uni6Dv2: Noise Elimination for 6D Pose Estimation},
  author={Mingshan Sun and Ye Zheng and Tianpeng Bao and Jianqiu Chen and Guoqiang Jin and Liwei Wu and Rui Zhao and Xiaoke Jiang},
  journal={ArXiv},
  year={2022},
  volume={abs/2208.06416}
}
Uni6D is the first 6D pose estimation approach to employ a unified backbone network to extract features from both RGB and depth images. We discover that the principal reasons of Uni6D performance limitations are Instance-Outside and Instance-Inside noise. Uni6D's simple pipeline design inherently introduces Instance-Outside noise from background pixels in the receptive field, while ignoring Instance-Inside noise in the input depth data. In this paper, we propose a two-step denoising approach… 
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