We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
您好,感谢您的开源,我有一些D设置方面的问题想问您。 首先,我观察到在训练中,您对参数的设置为640x512x128,interval=1.6。在测试中您的设置为1100x860x192,interval=0.8。而就您文中而言,您又用了1600x1184x256,interval=0.8来测试得出最终结果。在测试中不同的D(192,256)却有着同样的interval(0.8),会不会对结果造成影响呢? 其次,我想请问,D的选择和图像分辨率的大小是成一个正比的关系?如果说我在640*540的图像上用D=256.interval=0.8训练的话,是不是就不应该了。这个D的选择是您经过多次实验而得出的吗? 再次感谢您的开源~希望得到您的回复~
The text was updated successfully, but these errors were encountered:
internal越小结果应该会越准确。
training我没有仔细做过比较,不过D=128也可以得到好的结果,并且速度更快需要的显存也更小。
testing的话我在supplimentary material中有对比实验。
Sorry, something went wrong.
Hi,
For training @shubhamag have done an interesting study (#17 (comment)) on depth sample number.
No branches or pull requests
您好,感谢您的开源,我有一些D设置方面的问题想问您。
首先,我观察到在训练中,您对参数的设置为640x512x128,interval=1.6。在测试中您的设置为1100x860x192,interval=0.8。而就您文中而言,您又用了1600x1184x256,interval=0.8来测试得出最终结果。在测试中不同的D(192,256)却有着同样的interval(0.8),会不会对结果造成影响呢?
其次,我想请问,D的选择和图像分辨率的大小是成一个正比的关系?如果说我在640*540的图像上用D=256.interval=0.8训练的话,是不是就不应该了。这个D的选择是您经过多次实验而得出的吗?
再次感谢您的开源~希望得到您的回复~
The text was updated successfully, but these errors were encountered: