Smooth Animation

Smooth animation research aims to generate fluid and realistic motion, addressing challenges like jerky movements in robotics and artifacts in image and video processing. Current efforts focus on developing novel algorithms, including those based on thin-plate splines for interpolation, Riemannian flow matching for robot control, and neural ordinary differential equations for image-based animation, often incorporating regularization techniques to minimize abrupt changes. These advancements improve efficiency and realism in various applications, ranging from animation production and motion capture to autonomous robot control and the optimization of large language model inference.