AI RESEARCH

InterDyad: Interactive Dyadic Speech-to-Video Generation by Querying Intermediate Visual Guidance

arXiv CS.CV

ArXi:2603.23132v1 Announce Type: new Despite progress in speech-to-video synthesis, existing methods often struggle to capture cross-individual dependencies and provide fine-grained control over reactive behaviors in dyadic settings. To address these challenges, we propose InterDyad, a framework that enables naturalistic interactive dynamics synthesis via querying structural motion guidance. Specifically, we first design an Interactivity Injector that achieves video reenactment based on identity-agnostic motion priors extracted from reference videos. Building upon this, we.