Deep-Cross-Modal-Projection-Learning-for-Image-Text-Matching
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labyrinth7x
Why not ResNet
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 !
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%}
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