| Submission name | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Submission time (UTC) | Aug. 14, 2020, 7:55 a.m. | ||||||||||
| User | fbw19 | ||||||||||
| Task | 6D localization of seen objects | ||||||||||
| Dataset | YCB-V | ||||||||||
| Training model type | Fine | ||||||||||
| Training image type | Synthetic + real | ||||||||||
| Description | |||||||||||
| Evaluation scores |
|
| User | fbw19 |
|---|---|
| Publication | CDPN: Coordinates-Based Disentangled Pose Network for Real-Time RGB-Based 6-DoF Object Pose Estimation |
| Implementation | https://github.com/LZGMatrix/BOP19_CDPN_2019ICCV |
| Training image modalities | RGB |
| Test image modalities | RGB |
| Description | This method stays the same as Zhigang-CDPN-ICCV19 in BOP Challenge 2019. For LMO, HB, ICBIN and ITODD datasets, only PBR images provided for BOP Challenge 2020 were used during training. For YCBV, TUD and TLESS datasets, both PBR images provided for BOP Challenge 2020 and real images provided for BOP Challenge 2019 were used during training. |
| Computer specifications | CPU: Intel i7-7700; GPU: GTX 1070 |