| Submission name |
G2L_1_ICP
|
| Submission time (UTC) |
July 20, 2020, 11:03 p.m.
|
| User |
FindTruth_19
|
| Task |
6D localization of seen objects |
| Dataset |
TUD-L |
| Training model type |
Default |
| Training image type |
Real |
| Description |
Our method is based on G2L-CVPR2020. We add an ICP component to further improve the performance. We train three different networks for three objects but with same parameters. For both 2D detector and G2L, we only use real training images. For the 2D detector, we use YOLOv3 as the backbone and train 200 epochs. For G2L we train 10 epochs.
|
| Evaluation scores |
| AR: | 0.760 |
| AR_MSPD: | 0.828 |
| AR_MSSD: | 0.865 |
| AR_VSD: | 0.585 |
| average_time_per_image: | 0.225 |
|