We present BaRe-ESA, a novel Riemannian framework for human body scan representation, interpolation and extrapolation. BaRe-ESA operates directly on unregistered meshes, i.e., without the need to establish prior point to point correspondences or to assume a consistent mesh structure. Our method relies on a latent space representation, which is equipped with a Riemannian (non-Euclidean) metric associated to an invariant higher-order metric on the space of surfaces. Experimental results on the FAUST and DFAUST datasets show that BaRe-ESA brings significant improvements with respect to previous solutions in terms of shape registration, interpolation and extrapolation. The efficiency and strength of our model is further demonstrated in applications such as motion transfer and random generation of body shape and pose.
翻译:我们介绍Bare-ESA,这是一个关于人体扫描显示、内插和外推的新型里曼尼框架。Bare-ESA直接在未注册的模类上运作,即不需要事先确定点对准通信或采取一致的网状结构。我们的方法依赖于潜在的空间代表,它配备了一种里曼尼(非欧几里德)的度量,与地表空间的不变化的较高级度量有关。FAUST和DFAUST数据集的实验结果显示,巴雷-ESA在形状登记、内插和外推方面对以前的解决方案作出了重大改进。我们的模型的效率和力量在运动转移和随机生成身体形状和形状等应用中得到了进一步体现。