The emergence of text-to-image generator models has transformed the art industry, allowing anyone to create detailed artwork by providing text prompts. These AI models have gained recognition, won awards, and located applications in various media. Nevertheless, their widespread use has negatively impacted independent artists, displacing their work and undermining their ability to make a living.

Glaze has been developed to handle the problem of favor mimicry. Glaze enables artists to guard their unique styles by applying minimal perturbations, often known as “style cloaks,” to their artwork. These perturbations shift the representation of the artwork within the generator model’s feature space, teaching the model to associate the artist with a special style. In consequence, when AI models try and mimic the artist’s style, they generate artwork that doesn’t match the artist’s authentic style.

Glaze was developed in collaboration with skilled artists and underwent rigorous evaluation through user studies. Nearly all of surveyed artists found the perturbations to be minimal and never disruptive to the worth of their art. The system effectively disrupted style mimicry by AI models, even when tested against real-world mimicry platforms. Importantly, Glaze remained effective in scenarios where artists had already posted significant amounts of artwork online.

Glaze provides a technical solution to guard artists from style mimicry within the AI-dominated art landscape. Glaze offers an efficient defense mechanism by engaging with skilled artists and understanding their concerns. Glaze empowers artists to safeguard their artistic styles and maintain their creative integrity by applying minimal perturbations.

The system’s implementation involved computing rigorously designed style cloaks, which shift the artwork’s representation within the generator model’s feature space. Through training on multiple cloaked images, the generator model learns to associate the artist with a shifted artistic style, making it difficult for AI models to mimic the artist’s authentic style.

The effectiveness of Glaze was evaluated through user studies involving skilled artists. Nearly all of surveyed artists found the perturbations to be minimal and never disruptive to the worth of their art. The system successfully disrupted style mimicry by AI models, even when tested against real-world mimicry platforms. Glaze’s protection remained robust when artists shared significant amounts of artwork online.

In conclusion, Glaze offers a technical alternative to guard artists from style mimicry by AI models. Glaze has demonstrated its efficacy and usefulness through collaboration with skilled artists and user studies. By applying minimal perturbations, Glaze empowers artists to counteract style mimicry and preserve their artistic uniqueness within the face of AI-generated art.

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