Submission: DLZDet-PBR1/TUD-L/DLZDet-PBR1
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| Submission name |
DLZDet-PBR1
|
| Submission time (UTC) |
Oct. 16, 2022, 7:53 p.m.
|
| User |
USTC-IAT-United
|
| Task |
2D detection of seen objects |
| Dataset |
TUD-L |
| Training model type |
Default |
| Training image type |
Synthetic (only PBR images provided for BOP Challenge 2020 were used) |
| Description |
|
| Evaluation scores |
| AP: | 0.696 |
| AP50: | 0.932 |
| AP75: | 0.830 |
| AP_large: | 0.715 |
| AP_medium: | 0.701 |
| AP_small: | 0.875 |
| AR1: | 0.736 |
| AR10: | 0.787 |
| AR100: | 0.797 |
| AR_large: | 0.792 |
| AR_medium: | 0.797 |
| AR_small: | 0.925 |
| average_time_per_image: | -1.000 |
|
| User |
USTC-IAT-United
|
| Publication |
Title, Conference 2015. |
| Implementation |
MMDET |
| Training image modalities |
RGB |
| Test image modalities |
RGB |
| Description |
|
| Computer specifications |
3090 |