Among various interactions between humans, such as eye contact and gestures, physical interactions by contact can act as an essential moment in understanding human behaviors. Inspired by this fact, given a 3D partner human with the desired interaction label, we introduce a new task of 3D human generation in terms of physical contact. Unlike previous works of interacting with static objects or scenes, a given partner human can have diverse poses and different contact regions according to the type of interaction. To handle this challenge, we propose a novel method of generating interactive 3D humans for a given partner human based on a guided diffusion framework. Specifically, we newly present a contact prediction module that adaptively estimates potential contact regions between two input humans according to the interaction label. Using the estimated potential contact regions as complementary guidances, we dynamically enforce ContactGen to generate interactive 3D humans for a given partner human within a guided diffusion model. We demonstrate ContactGen on the CHI3D dataset, where our method generates physically plausible and diverse poses compared to comparison methods.

翻译：在人类的各种交互行为中，如眼神交流和手势，通过接触发生的物理交互可作为理解人类行为的重要时刻。受此启发，针对带有指定交互标签的三维伙伴人体，我们提出了一项基于物理接触的三维人体生成新任务。与以往与静态物体或场景交互的研究不同，给定的伙伴人体会根据交互类型呈现不同姿态和接触区域。为应对这一挑战，我们提出了一种基于引导扩散框架的新方法，用于为给定伙伴人体生成交互式三维人体。具体而言，我们新提出一个接触预测模块，该模块能根据交互标签自适应估计两个输入人体间的潜在接触区域。利用这些潜在接触区域的估计结果作为补充引导，我们在引导扩散模型中动态约束ContactGen为给定伙伴人体生成交互式三维人体。我们在CHI3D数据集上验证了ContactGen，结果表明相较对比方法，该方法能生成物理合理且多样化的姿态。