Motion Sequence

Motion sequence research focuses on generating and analyzing realistic human movements, often conditioned on textual descriptions, audio, or other contextual information. Current efforts heavily utilize diffusion models and transformers, often incorporating techniques like masked modeling, attention control, and discrete representations to improve motion quality, diversity, and temporal coherence. This field is crucial for advancements in animation, virtual reality, robotics, and human-computer interaction, enabling more natural and expressive interactions with digital environments and agents. The development of large, high-quality datasets is also a significant focus, driving improvements in model performance and generalization.