Modality-Agnostic Attention Fusion for visual search with text feedback
Table 6: Results on the Birds-to-Words and Spot-the-Diff test queries, with comparisons to baselines.
['Method', 'Birds-to-Words R10', 'Birds-to-Words R50', 'Spot-the-Diff R10', 'Spot-the-Diff R50']
Each of 3,347 image pairs has on average 4.8 paragraphs, each describing the differences between the pair of birds in an average of 32.1 tokens. Birds-to-Words provides richer text descriptions in each example than any of the other datasets we study, although the number of examples is small. Forbes et al. The baseline models are trained with the same parameters for the shared components, with the number of training iterations selected to optimize validation set performance. There are 17,672 image-image-caption triples from 8,566 image pairs in the training set, 3,310 triples from 1,493 image pairs in the validation set, and 2,107 triples from 1,270 image pairs in the test set. The dataset was originally designed to study relative caption generation, but it provides a challenging setting for our task since images from the same source are highly similar.