Perfusion | Nvidia

Discover the innovative approach of Key-Locked Rank One Editing with Perfusion, a groundbreaking text-to-image personalization method. Introduced by researchers from NVIDIA and Tel Aviv University and accepted to SIGGRAPH 2023, this technology tackles the complex challenges of personalizing text-to-image models. With a small additional model size of just 100KB per concept and a brief 4-minute training period, Perfusion excels in producing creatively personalized objects, allowing significant visual alterations without losing the object's core identity. The Key-Locking mechanism is instrumental in maintaining a consistent identity across images, while also enabling the combination of several learned concepts into one image. Furthermore, Perfusion delivers flexibility at inference time, balancing visual and textual harmony with a single trained model, stretching across the entire Pareto front without extra training. The method impresses with both qualitative and quantitative improvements over existing models, offering a new way to portray personalized object interactions.