Can Large Multimodal Models Uncover Deep Semantics Behind Images?

arXiv:2402.11281v1 Announce Type: new
Abstract: Understanding the deep semantics of images is essential in the era dominated by social media. However, current research works primarily on the superficial description of images, revealing a notable deficiency in the systematic investigation of the inherent deep semantics. In this work, we introduce DEEPEVAL, a comprehensive benchmark to assess Large Multimodal Models' (LMMs) capacities of visual deep semantics. DEEPEVAL includes human-annotated dataset and three progressive subtasks: fine-grained description selection, in-depth title matching, and deep …

abstract arxiv cs.cl current images investigation large multimodal models media multimodal multimodal models research semantics social social media type understanding work