# ZebraPose
The implementation of the paper 'ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation' (CVPR2022). [`ArXiv`](https://arxiv.org/abs/2203.09418)
## System Requirement
### Tested Environment
- Ubuntu 18.04
- CUDA 11.1
- Python 3.6
### Main Dependencies:
- [`bop_toolkit`](https://github.com/thodan/bop_toolkit)
- Pytorch 1.10
- torchvision 0.11.0
- opencv-python
- [`Progressive-X`](https://github.com/danini/progressive-x)
Download with `git clone --recurse-submodules` so that `bop_toolkit` will also be cloned.
## Training with a dataset in BOP benchmark
### Training data preparation
1. Download the dataset from [`BOP benchmark`](https://bop.felk.cvut.cz/datasets/)
2. Download required ground truth folders of zebrapose from [`owncloud`](https://cloud.dfki.de/owncloud/index.php/s/zT7z7c3e666mJTW). The folders are `models_GT_color`, `XX_G…
