Submission: DLZDet-PBR1/HB/DLZDet-PBR1
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| Submission name |
DLZDet-PBR1
|
| Submission time (UTC) |
Oct. 16, 2022, 7:07 p.m.
|
| User |
USTC-IAT-United
|
| Task |
Model-based 2D detection 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 |
| AP: | 0.777 |
| AP50: | 0.927 |
| AP75: | 0.862 |
| AP_large: | 0.800 |
| AP_medium: | 0.797 |
| AP_small: | 0.344 |
| AR1: | 0.807 |
| AR10: | 0.834 |
| AR100: | 0.838 |
| AR_large: | 0.941 |
| AR_medium: | 0.844 |
| AR_small: | 0.429 |
| 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 |