Topic Focus Articulation

Topic focus articulation research explores how to control and generate realistic representations of articulated objects and their movements, encompassing both physical objects (robotics) and virtual representations (e.g., 3D models, talking heads). Current research focuses on developing models, often leveraging deep learning techniques like diffusion models and graph neural networks, to synthesize and control articulated motion from various inputs such as images, speech, or semantic representations. This work has significant implications for robotics, computer graphics, and speech analysis, enabling advancements in areas like human-robot interaction, realistic avatar generation, and improved understanding of speech production and disorders.