视频模型全都不懂牛顿物理
最火的视频生成模型，画面漂亮，但物理一塌糊涂。新基准 Principia 用了一个聪明的办法测：不用管镜头焦距、物体大小这些变量，只看同一场景里两个物体是否遵循同一条物理定律——比如两个球从同一高度落下，落地时间就该一样。测了六个顶级视频生成器，最好的得分也只有 0.42(满分 1)，而它们在传统画质基准上都能拿 0.8。更扎心的是，让最强的视觉语言模型去判断视频里有没有物理错误，准确率只有 67%，大部分模型跟瞎猜差不多。这不是你明天能用上的东西，但它告诉你：现在 AI 生成的视频，只能看，不能信。
📄 原文摘要(英文)
Evaluating physical reasoning in video models is difficult because absolute motion measurements depend on frame rate, object scale, and camera calibration, all of which are often ambiguous or unavailable in generated video. We propose a different approach. When two objects in the same scene obey the same physical law, their motions must satisfy predictable relationships, and these relationships hold independent of calibration. We introduce Principia, a benchmark that evaluates Newtonian physics through relational consistency between paired objects. Principia spans eight phenomena - gravity, restitution, friction, rotational inertia, projectile motion, momentum, pendulum, and mass-spring oscillation - across translational, rotational, collisional, and oscillatory dynamics, using real-world scenes recorded under controlled protocols. We also introduce a calibration-independent consistency score that quantifies physical violation directly in image space. Across thousands of generations from six state-of-the-art video generators, no model exceeds 0.42 on Principia despite all scoring around 0.8 on VBench. Vision-language models are evaluated on their ability to detect relational physics violations, with the best model achieving only 67% accuracy and most performing near chance level.