USO: Unified Style and Subject-Driven Generation via Disentangled and Reward Learning
We announce USO, a unified style-subject optimized customization model and the latest addition to the UXO family.
USO can freely combine any subjects with any styles in any scenarios,
delivering outputs with high subject/identity consistency and strong style fidelity while ensuring natural, non-plastic portraits.
In line with our past practice, we will open-source the full project, including training code, inference scripts, model weights, and datasets,
to advance research and empower the open-source community.
https://bytedance.github.io/USO/