Parametric 3D body models like SMPL only represent minimally-clothed people and are hard to extend to clothing because they have a fixed mesh topology and resolution. To address these limitations, recent work uses implicit surfaces or point clouds to model clothed bodies. While not limited by topology, such methods still struggle to model clothing that deviates significantly from the body, such as skirts and dresses. This is because they rely on the body to canonicalize the clothed surface by reposing it to a reference shape. Unfortunately, this process is poorly defined when clothing is far from the body. Additionally, they use linear blend skinning to pose the body and the skinning weights are tied to the underlying body parts. In contrast, we model the clothing deformation in a local coordinate space without canonicalization. We also relax the skinning weights to let multiple body parts influence the surface. Specifically, we extend point-based methods with a coarse stage, that replaces canonicalization with a learned pose-independent "coarse shape" that can capture the rough surface geometry of clothing like skirts. We then refine this using a network that infers the linear blend skinning weights and pose dependent displacements from the coarse representation. The approach works well for garments that both conform to, and deviate from, the body. We demonstrate the usefulness of our approach by learning person-specific avatars from examples and then show how they can be animated in new poses and motions. We also show that the method can learn directly from raw scans with missing data, greatly simplifying the process of creating realistic avatars. Code is available for research purposes at {\small\url{https://qianlim.github.io/SkiRT}}.
翻译:类似 SMPL 的 3D 体型模型( 如 SMPL ), 仅代表最起码的穿衣人员, 很难扩展为衣着, 因为他们有固定的网状表层和分辨率。 为解决这些限制, 最近的工作使用隐含表面或指云云来模拟有衣体。 虽然不受地形学的限制, 此类方法仍然难以建模服装, 大大偏离身体, 如裙子和服装等。 这是因为它们依赖身体, 将衣物重新定位到一个参考形状, 使衣物表面变色。 不幸的是, 当衣物远离身体时, 这一过程就定义不清了。 此外, 它们使用线性混合皮质皮质皮质皮质皮质的皮质皮质剥离, 皮质重量被绑定。 相比之下, 我们将服装的变形变形体型建模建模在不光质化空间中, 使多身体部部分影响表面。 具体地说, 我们推广基于点制的“ 皮质” 形状,, 可以从底观察粗的表层测测测, 。 我们从底的体型化的体型化的体型化的体型模型的体型化方法可以显示一个模型的变变变的体力, 。