Neural 3D Articulation

Neural 3D articulation focuses on using deep learning to model and generate the movements of articulated objects, such as human speech organs or robotic limbs. Current research employs generative models like diffusion models and GANs, often incorporating attention mechanisms and graph-based representations to capture complex relationships between object parts and their movements. This field is significant for advancing speech synthesis by modeling the underlying articulatory processes, and for enabling more realistic and flexible animation of 3D models across diverse object categories, impacting robotics, computer graphics, and cognitive science.