3 papers
cs.CV2026
Interact2Ar: Full-Body Human-Human Interaction Generation via Autoregressive Diffusion Models
Pablo Ruiz-Ponce, Sergio Escalera, José GarcÃa-RodrÃguez +2
Generating realistic human-human interactions is a challenging task that requires not only high-quality individual body and hand motions, but also coherent coordination among all i…
cs.CV2025
MixerMDM: Learnable Composition of Human Motion Diffusion Models
Pablo Ruiz-Ponce, German Barquero, Cristina Palmero +2
Generating human motion guided by conditions such as textual descriptions is challenging due to the need for datasets with pairs of high-quality motion and their corresponding cond…
cs.CV2024
in2IN: Leveraging individual Information to Generate Human INteractions
Pablo Ruiz Ponce, German Barquero, Cristina Palmero +2
Generating human-human motion interactions conditioned on textual descriptions is a very useful application in many areas such as robotics, gaming, animation, and the metaverse. Al…