ArtHOI: 通过视频先验进行4D重建的可变形人-物交互合成
ArtHOI: Articulated Human-Object Interaction Synthesis by 4D Reconstruction from Video Priors
AI总结：
ArtHOI通过4D重建从视频先验生成可变形人-物交互，提升接触精度和物理合理性。
摘要：
合成在没有3D/4D监督的情况下具有物理合理性的可变形人-物交互（HOI）仍然是一个根本性挑战。尽管最近的零样本方法利用视频扩散模型来合成人-物交互，但它们大多局限于刚性物体操作，并缺乏显式的4D几何推理。为弥合这一差距，我们将可变形HOI合成 formulations 为从单目视频先验进行4D重建的问题：仅给定一个由扩散模型生成的视频，我们重建一个完整的4D可变形场景，而无需任何3D监督。这种基于重建的方法将生成的2D视频作为逆渲染问题的监督，恢复几何一致且物理合理的4D场景，这些场景自然尊重接触、可变形性和时间一致性。我们介绍了ArtHOI，这是首个通过从视频先验进行4D重建来合成可变形人-物交互的零样本框架。我们的关键设计是：1）基于流的部分分割：利用光流作为几何线索，将单目视频中的动态区域与静态区域解耦；2）解耦的重建流程：联合优化人体运动和物体可变形性在单目模糊下不稳定，因此我们首先恢复物体可变形性，然后在重建的物体状态下合成人体运动。ArtHOI连接了基于视频的生成和几何感知的重建，生成的交互在语义上一致且在物理上合理。在多样化的可变形场景（如打开冰箱、柜子、微波炉）中，ArtHOI在接触准确性、穿透减少和可变形性保真度方面显著优于先前方法，通过重建引导的合成将零样本交互合成扩展到刚性操作之外。
英文摘要：
Synthesizing physically plausible articulated human-object interactions (HOI) without 3D/4D supervision remains a fundamental challenge. While recent zero-shot approaches leverage video diffusion models to synthesize human-object interactions, they are largely confined to rigid-object manipulation and lack explicit 4D geometric reasoning. To bridge this gap, we formulate articulated HOI synthesis as a 4D reconstruction problem from monocular video priors: given only a video generated by a diffusion model, we reconstruct a full 4D articulated scene without any 3D supervision. This reconstruction-based approach treats the generated 2D video as supervision for an inverse rendering problem, recovering geometrically consistent and physically plausible 4D scenes that naturally respect contact, articulation, and temporal coherence. We introduce ArtHOI, the first zero-shot framework for articulated human-object interaction synthesis via 4D reconstruction from video priors. Our key designs are: 1) Flow-based part segmentation: leveraging optical flow as a geometric cue to disentangle dynamic from static regions in monocular video; 2) Decoupled reconstruction pipeline: joint optimization of human motion and object articulation is unstable under monocular ambiguity, so we first recover object articulation, then synthesize human motion conditioned on the reconstructed object states. ArtHOI bridges video-based generation and geometry-aware reconstruction, producing interactions that are both semantically aligned and physically grounded. Across diverse articulated scenes (e.g., opening fridges, cabinets, microwaves), ArtHOI significantly outperforms prior methods in contact accuracy, penetration reduction, and articulation fidelity, extending zero-shot interaction synthesis beyond rigid manipulation through reconstruction-informed synthesis.
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