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@ildoonet
ildoonet committed Jun 4, 2018
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## COCO Datasets

| Set | Model | Scale | AP | AP 50 | AP 75 | AP medium | AP large | AR | AR 50 | AR 75 | AR medium | AR large |
|-------------|----------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|
| Validation | Original Paper | Multi | 0.584 | 0.815 | 0.693 | 0.544 | 0.651 | | | | | |
| Set | Model | Scale | Resolution | AP | AP 50 | AP 75 | AP medium | AP large | AR | AR 50 | AR 75 | AR medium | AR large |
|-------------|----------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|
| 2014 Val | Original Paper | 3 | Image | 0.584 | 0.815 | 0.693 | 0.544 | 0.651 | | | | | |
| | | | | | | | | | | | | |
| Validation | CMU | Single | 0.5067 | 0.7660 | 0.5377 | 0.4927 | 0.5309 | 0.5614 | 0.7900 | 0.5903 | 0.5089 | 0.6347 |
| Validation | Mobilenet thin | Single | 0.2806 | 0.5577 | 0.2474 | 0.2802 | 0.2843 | 0.3214 | 0.5840 | 0.2997 | 0.2946 | 0.3587 |
| 2014 Val | CMU | 1 | Image | 0.5067 | 0.7660 | 0.5377 | 0.4927 | 0.5309 | 0.5614 | 0.7900 | 0.5903 | 0.5089 | 0.6347 |
| 2014 Val | Mobilenet thin | 1 | Image | 0.2806 | 0.5577 | 0.2474 | 0.2802 | 0.2843 | 0.3214 | 0.5840 | 0.2997 | 0.2946 | 0.3587 |

I also ran keras & caffe models to verify single-scale version's performance, they matched this result.

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