Understanding Image Captioning Models beyond Visualizing Attention
TABLE VI: The performance of the models tuned with LRP (L.-*) and without LRP inference evaluated on the balanced clothes-subset and person-subset of Flickr30K. The evaluation metrics include FB: FBERT(idf), C: CIDEr, S: SPICE, R-L: ROUGE-L, M: METEOR.
['clothes', '[ITALIC] FB', 'C', 'S', 'R-L', 'M']
Although LRP-inference does not improve the performance over the original test set, we find a constant improvement of LRP-inference models on the relatively balanced subsets, especially for adaptive attention model on the clothes-subset where we gain 2.38 CIDEr score after fine-tuning.