Relation-aware Hierarchical Attention Framework for Video Question Answering

• Published in: arXiv.org
• Main Authors: Li, Fangtao, Bai, Ting, Cao, Chenyu, Liu, Zihe, Yan, Chenghao, Wu, Bin
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 14.05.2021
• Subjects: Coders; Computer Science - Artificial Intelligence; Computer Science - Computer Vision and Pattern Recognition; Feature extraction; Frames (data processing); Object recognition; Questions; Video

Video Question Answering (VideoQA) is a challenging video understanding task since it requires a deep understanding of both question and video. Previous studies mainly focus on extracting sophisticated visual and language embeddings, fusing them by delicate hand-crafted networks. However, the releva...