Knowledge-Based Video Question Answering with Unsupervised Scene Descriptions
Table 6: Character Recognition accuracy on 100 random frames.
['[EMPTY]', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F1-score']
We evaluate the performance of the different video modules used in the observe branch. As datasets in video story question answering do not generally contain annotations on characters, places, objects relationships or actions, accuracy results are difficult to obtain. Even so, we report accuracy for the Character Recognition For the Character Recognition, we randomly annotate a subset of 100 video frames and measure accuracy as the number of correct predictions before and after applying the spatio-temporal filter. For the Place Classification, we report accuracy before and after the temporal filter on the KnowIT VQA test set according to the labels obtained from the scripts. Additionally, visual results with the predictions from the four modules (Character Recognition, Place Classification, Object Relation Detection, and Action Recognition) are in Fig. Finally, the list of characters and places can be found in Tables