Text-to-Image-to-Text Translation using Cycle Consistent Adversarial Networks
Table 2: Image color relevance score for the two models
['Model', 'Color relevance score']
To analyze the effectiveness of our method further, we manually find the ratio of number of colors that are present in each image to all the colors that were mentioned in the caption. We average this number over 30 random images generated by our GAN model trained with cycle consistency and trained without cycle consistency. We observe significant improvement in our model’s ability to generate the images with colors as described in the caption.