Comment-aided Video-Language Alignment via Contrastive Pre-training for Short-form Video Humor Detection

arXiv:2402.09055v2 Announce Type: replace
Abstract: The growing importance of multi-modal humor detection within affective computing correlates with the expanding influence of short-form video sharing on social media platforms. In this paper, we propose a novel two-branch hierarchical model for short-form video humor detection (SVHD), named Comment-aided Video-Language Alignment (CVLA) via data-augmented multi-modal contrastive pre-training. Notably, our CVLA not only operates on raw signals across various modal channels but also yields an appropriate multi-modal representation by aligning the video and language …

alignment arxiv cs.ai cs.cv detection form humor language pre-training training type via video