Texvent：基于文本提示的异步事件数据仿真
Texvent: Asynchronous Event Data Simulation via Text Prompt
用多模态大模型按文本提示渲染视频，再经物理仿真器转成异步事件流，为事件相机视觉任务提供低成本、可扩展的合成数据管线；其中自适应亮度感知帧插值与基于缓存的电压刷新机制可直接复用于事件数据增广与仿真器改进。
原文依据 we propose a Text-to-event simulation framework (Texvent) that can directly generate asynchronous event data from simple text prompts
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论当前的事件仿真方法主要利用视频来合成新的事件数据，但面临视频采集成本高、在视角、运动和光照方面可扩展性有限的问题。为此，我们提出了一个文本到事件仿真框架（Texvent），能够直接从简单的文本提示生成异步事件数据。Texvent 首先通过多模态大语言模型渲染由提示驱动的视频，随后应用一个新的物理仿真器生成事件流。具体而言，我们提出了一种自适应亮度感知的帧插值方法，以提升渲染视频的时序分辨率。仿真器中引入了平衡对数强度比较策略和基于缓存的电压刷新机制，以生成事件数据。为缩小仿真到现实的差距，我们还引入了背景活动噪声注入和稠密时间戳重建操作。大量实验表明，Texvent 具有更优的计算效率，并且相比现有仿真器能够生成更真实的事件数据。
英文原文摘要 1087 字符
Current event simulation methods focus on employing videos to synthesize new event data, suffering from costly video capture and limited scalability across viewpoints, motions, and lighting. To this end, we propose a Text-to-event simulation framework (Texvent) that can directly generate asynchronous event data from simple text prompts. Texvent first renders prompt-driven videos via multimodal large language models and subsequently applies a new physical simulator to generate event streams. Specifically, an adaptive brightness-aware frame interpolation approach is proposed to enhance the temporal resolution of the rendered videos. A balanced logarithmic intensity comparison strategy and a cache-based voltage refreshment mechanism are introduced into the simulator to generate event data.To narrow the sim-to-real gap, we also introduce background activity noise injection and dense time stamp reconstruction operations. Extensive experiments demonstrate Texvent's superior computational efficiency and its ability to generate more realistic event data than existing simulators.