PROMPT RADAR / VIDEO视频叙事

I wanted to see how far AI video could actually go when you give it a re

I wanted to see how far AI video could actually go when you give it a real cinematic story. So I started with one simple idea: a lone astronaut standing on an unknown planet, watching a massive spacecraft emerge from beh

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它为什么值得进入灵感库

先别急着照抄整段 Prompt:真正有用的是主体、空间和镜头之间的约束关系。 把一段描述拆成起始状态、动作变化、镜头响应和结束画面,连续性比形容词更重要。

动作与镜头 Prompt

I wanted to see how far AI video could actually go when you give it a real cinematic story. So I started with one simple idea: a lone astronaut standing on an unknown planet, watching a massive spacecraft emerge from behind the mountains. Then I built the scene with **Seedance 2.5 on Morphic**. The goal wasn’t just to generate a pretty shot. I wanted the whole sequence to feel like one continuous scene — the same character, the same environment, consistent lighting, realistic ocean reflections, atmospheric movement, and a spacecraft that actually feels massive. What surprised me most was how much control you can get over the storytelling. I could take the scene from a wide cinematic establishing shot → to the astronaut’s reaction → to the spacecraft reveal → and finally into a massive energy portal over the ocean. And the best part? I didn’t need a camera, actors, a film crew, or a huge VFX setup. Just the idea, the prompt, and **Morphic**. This is the kind of AI video workflow that makes you rethink what a solo creator can actually produce. Seedance 2.5 is now available on @morphic What would you create with it? 👀
查看原作者内容

不要一次改完所有变量

用 Seedance 复刻时,建议先单独生成稳定首帧,再把动作拆成“开始、变化、收束”三段;每段只保留一个主要运动。

  1. 主体:I wanted to see how far AI video could actually go when you give it a real cinematic story. So I started with one simple idea: a lone astronaut standing on an unknown planet, watching a massive spacecraft emerge from beh
  2. 视觉方向:实时 AI 视频案例;查看原帖媒体与作者说明
  3. 镜头与构图:按原帖镜头流程执行;查看原帖媒体与工作流
  4. 交付约束:auto,保留原作者方法与归属;复刻时避免水印、低清、畸变、主体漂移和无关文字。
负向约束

保留原作者方法与归属;复刻时避免水印、低清、畸变、主体漂移和无关文字。

模型建议

Seedance / Veo / Kling。先用原始 Prompt 建立基准结果,再根据模型对自然语言、镜头运动或文字排版的能力做局部改写。

来源与编辑原则

保留作者,也保留判断。

本页收录公开案例并提供中文索引、结构化拆解和复刻建议,不冒充原作者作品,也不替代原帖上下文。

作者:Scarlett · 收录于 2026年8月14日

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