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Expect dw to bring more gain in yolov6!

Open meituan-gengyifei opened this issue 2 years ago • 2 comments

hi, we are interested in your work, and you are welcome to add dw's work to our yolov6 for even greater gainshttps://github.com/meituan/YOLOv6 We actually tried it on yolov6n using the dw you open sourced on fcos. But the effect is not ideal. When the box-refine branch is used, it will drop by 1.1map, and when the box-refine branch is not used, it will drop by 1.6map. This may be due to your special design for the fcos network, or the yolov6n network is too lightweight. So I expect you to introduce more targeted dw on yolov6 to improve the effect.

meituan-gengyifei avatar Jun 29 '22 06:06 meituan-gengyifei

Thanks for your interests in our work. We will try to apply dw on yolov6 in the coming days.

strongwolf avatar Jun 29 '22 07:06 strongwolf

Hi, What do you use to draw the Sample Weighting diagram?

justin14567 avatar Nov 10 '22 07:11 justin14567