| Submission name | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Submission time (UTC) | Aug. 18, 2020, 7:15 p.m. | ||||||||||
| User | yann_labbe | ||||||||||
| Task | 6D localization of seen objects | ||||||||||
| Dataset | HB | ||||||||||
| 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 | yann_labbe |
|---|---|
| Publication | Labbé et al, CosyPose: Consistent multi-view multi-object 6D pose estimation, ECCV 2020 |
| Implementation | https://github.com/ylabbe/cosypose |
| Training image modalities | RGB |
| Test image modalities | RGB |
| Description | Full multi-view method described in the paper, ran with 4 views and using detections and pose estimation models of CosyPose-ECCV20-SYNT+REAL-1VIEW (slightly different from the paper). Computation time for each group of image is divided by the number of images. |
| Computer specifications | CPU: 20-core Intel Xeon 6164 @ 3.2 GHz, GPU: Nvidia V100 |