Neural network (NN) models have achieved state-of-the-art performance on several image tasks overthelastfewyears.

In this work, we significantly improve this framework by proposing an extremely compact parameter space for fine-tuning the generator.

By applying a single blur operation, we can retain more spatial relevance information. Moreover, since the images are blurred, they may have a relatively minor impact on the recognition ability of CLIP on the target.