展望叙事智能：创意视觉故事讲述选集
Envisioning Narrative Intelligence: A Creative Visual Storytelling Anthology
AI总结：
该研究收集100篇即兴视觉故事构建的作品，分析得出五大创作差异主题，并据此提出计算视觉故事讲述的叙事智能五大标准，为自动故事生成的训练数据收集与发展提供参考。
摘要：
本文收集了100篇视觉故事选集，这些故事来自参与我们基于图像序列的即兴故事构建系统性创作流程的作者。通过对选集进行文本细读与主题分析，我们提出了五个主题，用以刻画这一创意视觉故事讲述过程中呈现的差异：（1）叙述视觉所见 vs 展望想象；（2）动态刻画实体/物体特征；（3）感知场景的体验式信息；（4）调节情绪氛围；（5）编码叙事偏差。为理解人们从图像中衍生故事的多样方式，我们为收集故事驱动的训练数据提供了考量方向，以为自动故事生成提供参考。对应每个主题，我们提出计算视觉故事讲述的叙事智能标准为：创意性、可靠性、表达性、 grounded（ grounded 此处指具身性/落地性，保留术语语境）、负责任。基于这些标准，我们讨论了如何突出创意表达、考量偏差，并在视觉故事世界的边界内运作。
英文摘要：
In this paper, we collect an anthology of 100 visual stories from authors who participated in our systematic creative process of improvised story-building based on image sequences. Following close reading and thematic analysis of our anthology, we present five themes that characterize the variations found in this creative visual storytelling process: (1) Narrating What is in Vision vs. Envisioning; (2) Dynamically Characterizing Entities/Objects; (3) Sensing Experiential Information About the Scenery; (4) Modulating the Mood; (5) Encoding Narrative Biases. In understanding the varied ways that people derive stories from images, we offer considerations for collecting story-driven training data to inform automatic story generation. In correspondence with each theme, we envision narrative intelligence criteria for computational visual storytelling as: creative, reliable, expressive, grounded, and responsible. From these criteria, we discuss how to foreground creative expression, account for biases, and operate in the bounds of visual storyworlds.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
