标题： 学习生成物理引导的视频扩散对象交互 显示英文标题

标题： Learning to Generate Object Interactions with Physics-Guided Video Diffusion

摘要： 最近的视频生成模型取得了显著进展，并已应用于电影、社交媒体制作和广告中。 除了其创造潜力外，这些模型在机器人和具身决策的世界模拟器方面也展现出前景。 尽管取得了显著进展，但目前的方法仍然难以生成物理上合理的物体交互，并缺乏基于物理的控制机制。 为解决这一限制，我们引入了KineMask，这是一种用于物理引导视频生成的方法，能够实现真实的刚体控制、交互和效果。 给定一张图像和指定的物体速度，我们的方法生成具有推断运动和未来物体交互的视频。 我们提出了一种两阶段训练策略，通过物体掩码逐步移除未来运动监督。 使用这种策略，我们在简单交互的合成场景上训练视频扩散模型（VDMs），并在真实场景中展示了物体交互的显著改进。 此外， KineMask通过预测场景描述将低层次运动控制与高层次文本条件结合，从而有效支持复杂动态现象的合成。 大量实验表明， KineMask在与近期同类模型相比时表现出显著提升。 消融研究进一步突显了VDMs中低层次和高层次条件的互补作用。 我们的代码、模型和数据将公开提供。 显示英文摘要

摘要： Recent models for video generation have achieved remarkable progress and are now deployed in film, social media production, and advertising. Beyond their creative potential, such models also hold promise as world simulators for robotics and embodied decision making. Despite strong advances, however, current approaches still struggle to generate physically plausible object interactions and lack physics-grounded control mechanisms. To address this limitation, we introduce KineMask, an approach for physics-guided video generation that enables realistic rigid body control, interactions, and effects. Given a single image and a specified object velocity, our method generates videos with inferred motions and future object interactions. We propose a two-stage training strategy that gradually removes future motion supervision via object masks. Using this strategy we train video diffusion models (VDMs) on synthetic scenes of simple interactions and demonstrate significant improvements of object interactions in real scenes. Furthermore, KineMask integrates low-level motion control with high-level textual conditioning via predictive scene descriptions, leading to effective support for synthesis of complex dynamical phenomena. Extensive experiments show that KineMask achieves strong improvements over recent models of comparable size. Ablation studies further highlight the complementary roles of low- and high-level conditioning in VDMs. Our code, model, and data will be made publicly available.