Why not ResNet

[FangmingZhou]

Notice that the results in paper 'Deep Cross-Modal Pojection Learning for Image-Text Matching' are:{top- 1 = 49.37%，top-10 = 79.27%}
while the results in this project are {top- 1 = 42.999%,top-10 = 67.869%}, which are resulted from the model that is based on MobileNet.
So, why not provide a new version that is based on ResNet! ^^ It will be greatly helpful for our beginners ! Thanks a lot !

[wxh001qq]

Hello, is your results based on CUHK-PEDES?

[FangmingZhou]

Hello, is your results based on CUHK-PEDES?

yes

[wxh001qq]

Hello, is your results based on CUHK-PEDES?

yes

I found whether to use nn.DataParallel() will extremely influence the result.
if not use nn.DataParallel() got about {top- 1 = 31%，top-10 = 55%}
while use got about {top- 1 = 42%，top-10 = 67%}

[FangmingZhou]

Hello, is your results based on CUHK-PEDES?

yes

I found whether to use nn.DataParallel() will extremely influence the result.
if not use nn.DataParallel() got about {top- 1 = 31%，top-10 = 55%}
while use got about {top- 1 = 42%，top-10 = 67%}

我没有用过并行的这个方法，网上好像也没有提到这会导致结果不同的？可能你要请教一下别人了