José García-Rodríguez — accepted AI-conference papers

2026

Interact2Ar: Full-Body Human-Human Interaction Generation via Autoregressive Diffusion Models

Pablo Ruiz-Ponce, Sergio Escalera, José García-Rodríguez, Jiankang Deng, Rolandos Alexandros Potamias

CVPR 2026

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 interactants. Due to limitations in available data and increased learning complexity, previous methods tend to ignore han

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2025

MixerMDM: Learnable Composition of Human Motion Diffusion Models

Pablo Ruiz-Ponce, German Barquero, Cristina Palmero, Sergio Escalera, José García-Rodríguez

CVPR 2025poster

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 conditions. The difficulty increases when aiming for finer control in the generation. To that end, prior works have proposed…

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