How to reach the mAP on Maskrcnn paper?

[yiyang186]

I used the project to train on coco train 2014. And I got the evaluation:

loading annotations into memory... Done (t=4.37s) creating index... index created! 40504 40504 Loading and preparing results... DONE (t=11.58s) creating index... index created! Running per image evaluation... Evaluate annotation type keypoints DONE (t=147.12s). Accumulating evaluation results... DONE (t=1.72s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.229 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets= 20 ] = 0.614 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets= 20 ] = 0.116 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.191 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = 0.281 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.310 Average Recall (AR) @[ IoU=0.50 | area= all | maxDets= 20 ] = 0.686 Average Recall (AR) @[ IoU=0.75 | area= all | maxDets= 20 ] = 0.241 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.259 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = 0.378

How do I train to mAP(kp, 50)=80+ on maskrcnn paper?

[chenyanyin]

i want to know,too