Equivariant and Invariant Grounding for Video Question Answering
Yicong Li, Xiang Wang, Junbin Xiao, Tat‐Seng Chua · Proceedings of the 30th ACM International Conference on Multimedia · 2022
Video Question Answering (VideoQA) is the task of answering the natural language questions about a video. Producing an answer requires understanding the interplay across visual scenes in video and linguistic semantics in question. However, most leading VideoQA models work as black boxes, which make the visual-linguistic alignment behind the answering process obscure. Such black-box nature calls for visual explainability that reveals "What part of the video should the model look at to answer the question?". Only a few works present the visual explanations in a post-hoc fashion, which emulates the target model's answering process via an additional method.