| Submission name | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Submission time (UTC) | Oct. 14, 2022, 5:03 p.m. | ||||||||||
| User | zebrapose | ||||||||||
| Task | 6D localization of seen objects | ||||||||||
| Dataset | ITODD | ||||||||||
| Training model type | Default | ||||||||||
| Training image type | Synthetic (only PBR images provided for BOP Challenge 2020 were used) | ||||||||||
| Description | |||||||||||
| Evaluation scores |
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| User | zebrapose |
|---|---|
| Publication | ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation, CVPR2022 |
| Implementation | https://github.com/suyz526/ZebraPose |
| Training image modalities | RGB |
| Test image modalities | RGB |
| Description | Arxiv: https://arxiv.org/abs/2203.09418 We fixed a bug which influence the inference stage of Tless. The bug has been fixed on 17.Oct.2022. This new score is calculated using the same checkpoints. The old score was 0.603. The reported inference time included 2D detection time. |
| Computer specifications | Intel(R) Xeon(R) E-2146G CPU @ 3.50GHz, Nvidia RTX2080Ti |