GROOViST: A Metric for Grounding Objects in Visual Storytelling
원문 초록
A proper evaluation of stories generated for a sequence of images -- the task commonly referred to as visual storytelling -- must consider multiple aspects, such as coherence, grammatical correctness, and visual grounding. In this work, we focus on evaluating the degree of grounding, that is, the extent to which a story is about the entities shown in the images. We analyze current metrics, both designed for this purpose and for general vision-text alignment. Given their observed shortcomings, we propose a novel evaluation tool, GROOViST, that accounts for cross-modal dependencies, temporal misalignments (the fact that the order in which entities appear in the story and the image sequence may not match), and human intuitions on visual grounding. An additional advantage of GROOViST is its modular design, where the contribution of each component can be assessed and interpreted individually.
함께 살펴볼 논문
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VIST-GPT: Ushering in the Era of Visual Storytelling with LLMs?
SCO-VIST: Social Interaction Commonsense Knowledge-based Visual Storytelling
GTA1: GUI Test-time Scaling Agent
High-Resolution Visual Reasoning via Multi-Turn Grounding-Based Reinforcement Learning
DenseWorld-1M: Towards Detailed Dense Grounded Caption in the Real World
토론
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