Video captioning with stacked attention and semantic hard pull.

ABSTRACT: Video captioning, i.e., the task of generating captions from video sequences creates a bridge between the Natural Language Processing and Computer Vision domains of computer science. The task of generating a semantically accurate description of a video is quite complex. Considering the complexity, of the problem, the results obtained in recent research works are praiseworthy. However, there is plenty of scope for further investigation. This paper addresses this scope and proposes a novel solution. Most video captioning models comprise two sequential/recurrent layers-one as a video-to-context encoder and the other as a context-to-caption decoder. This paper proposes a novel architecture, namely Semantically Sensible Video Captioning (SSVC) which modifies the context generation mechan

SUBMITTER: Rahman MM 

PROVIDER: S-EPMC8356660 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature