用连续力控实现物理真实感的实时视频生成
Streaming Video Generation with Streaming Force Control
- 统一力信号表示，支持因果实时响应各类动态力输入
- 单卡最高16.6帧/秒，力控遵循与运动真实度达当前最佳
- 适合交互式视频生成、物理模拟与人机协同场景
我们提出StreamForce，一种流式视频生成框架，通过连续力输入实现物理基础控制。与以往需为不同力类型训练独立模型、假设力恒定或依赖非因果处理的方法不同，StreamForce是因果且统一的模型，能即时、连贯地响应局部与全局、随时间变化的力。为此，我们设计统一力表示作为控制信号，并开发力可控视频生成的蒸馏流程。模型结合自回归效率与力响应能力，保持稳定的图像真实感与动态一致性。StreamForce在单张GPU上运行速度可达16.6 FPS，力控遵循性与运动真实度均达到当前最优水平。
原文摘要 · Abstract (English)
We introduce StreamForce, a streaming video generation framework that enables physically grounded control through continuous force inputs. Unlike prior video models that train separate models for different force types, assume fixed forces, or rely on non-causal processing, StreamForce is a causal and unified model that responds instantly and coherently to both local and global, time-varying forces. To achieve this, we design a unified force representation as a control signal and develop a distillation pipeline for force-controllable video generation. Our model combines autoregressive efficiency with force responsiveness, sustaining stable photometric and dynamic realism. StreamForce runs at up to 16.6 FPS on a single GPU, achieving state-of-the-art performance in both force adherence and motion realism. Project website: https://neu-vi.github.io/StreamForce/
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