4Deform: Neural Surface Deformation for Robust Shape Interpolation

Figure 1. 4Deform takes a sparse temporal sequence of point clouds as input and generates realistic intermediate shapes. Starting from just pairs of point clouds and estimated sparse, noisy correspondences (indicated using colors in the point clouds), our method obtains realistic long-range interpolations, even for shapes with changing topology (e.g., the human-object interaction in the top row), and can generalize the interpolation results to real-world data (Kinect point clouds in the second row). Meanwhile, our method can handle non-isometrically deformed shapes (bottom left) as well as partial shapes (bottom right).