| User | thodan |
|---|---|
| Publication | Hodan, Barath, Matas, EPOS: Estimating 6D Pose of Objects with Symmetries, CVPR 2020 |
| Implementation | https://github.com/thodan/epos |
| Training image modalities | RGB |
| Test image modalities | RGB |
| Description | Only the synthetic "PBR-BlenderProc4BOP" RGB images provided for the BOP Challenge 2020 were used for training. The results were achieved without any post-refinement of the estimated poses (i.e. without ICP, DeepIM, etc.). Up to 5000 2D-3D correspondences with the highest confidence were used per image. Other hyper-parameters were set as described in the CVPR 2020 paper. |
| Computer specifications | 14-core Intel Xeon E5-2680 v4 CPU, 252GB RAM, Nvidia P100 GPU |
| Date | Submission name | Dataset | ||
|---|---|---|---|---|
| 2020-08-19 18:26 | - | HB | ||
| 2020-08-19 18:27 | - | IC-BIN | ||
| 2020-08-19 18:27 | - | ITODD | ||
| 2020-08-19 18:27 | - | LM-O | ||
| 2020-08-19 18:29 | - | TUD-L | ||
| 2020-08-19 18:31 | - | YCB-V | ||
| 2020-08-19 19:35 | - | T-LESS |