Based on the paper "ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation", CVPR 2022.

• Training images: PBR image + Real images (if available)

• Setting: One network per object was trained

• 2D Bounding Box: FCOS detection results provided by CDPNv2

• Modifications to the original ZebraPose paper:

  1. Added Symmetry-Aware Training (SAT). The network and loss functions are not changed. There will be a new ground truth for the sym. objects, details can be found in the Github Repository. Special thanks to Yongliang Lin for his contribution.

• The reported inference time included 2D detection time.

List of contributors:

• German Research Center for Artificial Intelligence (DFKI), Augmented Vision department:

Yongzhi Su, Praveen Nathan, Torben Fetzer, Jason Rambach, Didier Stricker

• Technical University Munich (TUM), CAMPAR:

Mahdi Saleh, Yan Di, Nassir Navab, Benjamin Busam, Federico Tombari

• Zhejiang University (ZJU):

Yongliang Lin, Yu Zhang