[论文] Reading, Writing, Sharing, and Interacting with the World through Vide...
研究领域: CV 作者: Shengqiong Wu, Meng Luo, Bobo Li, Ziwei Liu, Shuicheng Yan, Ming-Hsuan Yang, Philip Torr, Hao Fei 发布时间: 2026-10-22 arXiv: 2610.31668
论文概要
研究领域: CV 作者: Shengqiong Wu, Meng Luo, Bobo Li, Ziwei Liu, Shuicheng Yan, Ming-Hsuan Yang, Philip Torr, Hao Fei 发布时间: 2026-10-22 arXiv: 2610.31668
中文摘要
视频基础模型在理解和生成视觉序列方面发展迅速,而视频世界模型则试图捕捉其所描绘世界的底层动力学。尽管目标不同,两者都关注视频观测与演化世界之间的关系。本篇综述以世界建模为统一视角来审视这些进展。将观测到的视频视为潜在时间世界的部分、有损且按时间顺序排列的投影,我们围绕四种互补操作组织文献:「读」从观测视频中推断世界属性;「写」从指定或学习到的世界条件合成视频;「共享」通过共同的建模机制整合理解与生成;「交互」在动作和演化观测下预测和更新世界状态。这一视角区分了观测或生成序列中的时间一致性与底层世界状态的一致性。我们追溯了从片段级识别和感知保真度向持久状态、可控演化、物理与因果有效性以及基于交互和下游决策的评估的转变,并提炼出随之而来的开放挑战。
原文摘要
Video foundation models have advanced rapidly in understanding and generating visual sequences, while video world models seek to capture the underlying dynamics of the world they depict. Despite their different objectives, both concern the relationship between video observations and an evolving world. This survey adopts world modeling as a unifying lens for examining these developments. Viewing an observed video as a partial, lossy, and temporally ordered projection of a latent temporal world, we organize the literature around four complementary operations: reading infers world properties from observed video; writing synthesizes video from specified or learned world conditions; sharing integrates understanding and generation through common modeling mechanisms; and interacting predicts and ...
*自动采集于 2026-10-24*
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