Video question answering is an increasingly vital research field, spurred by the rapid
proliferation of video content online and the urgent need for intelligent systems that can …

In this paper, we propose a novel end-to-end trainable Video Question Answering
(VideoQA) framework with three major components: 1) a new heterogeneous memory which …

Significant advancements in video question answering (VideoQA) have been made thanks
to thriving large image-language pretraining frameworks. Although these image-language …

Video Question Answering (VideoQA) is a challenging problem, as it requires a joint
understanding of video and natural language question. Existing methods perform correlation …

Significant advancements in video question answering (VideoQA) have been made thanks
to thriving large image-language pretraining frameworks. Although these image-language …

Video Question Answering (VideoQA) aims to comprehend intricate relationships, actions,
and events within video content, as well as the inherent links between objects and scenes …

This paper presents a novel method, termed Bridge to Answer, to infer correct answers for
questions about a given video by leveraging adequate graph interactions of heterogeneous …

This paper identifies two kinds of redundancy in the current VideoQA paradigm. Specifically,
the current video encoders tend to holistically embed all video clues at different granularities …

Video question answering (VideoQA) is challenging given its multimodal combination of
visual understanding and natural language understanding. While existing approaches …

Video Question Answering (VideoQA) has emerged as a challenging frontier in the field of
multimedia processing, requiring intricate interactions between visual and textual modalities …