4 papers
Efficiency without Compromise: CLIP-aided Text-to-Image GANs with Increased Diversity
Yuya Kobayashi, Yuhta Takida, Takashi Shibuya +1
Recently, Generative Adversarial Networks (GANs) have been successfully scaled to billion-scale large text-to-image datasets. However, training such models entails a high training…
Forging and Removing Latent-Noise Diffusion Watermarks Using a Single Image
Anubhav Jain, Yuya Kobayashi, Naoki Murata +6
Watermarking techniques are vital for protecting intellectual property and preventing fraudulent use of media. Most previous watermarking schemes designed for diffusion models embe…
TraSCE: Trajectory Steering for Concept Erasure
Anubhav Jain, Yuya Kobayashi, Takashi Shibuya +4
Recent advancements in text-to-image diffusion models have brought them to the public spotlight, becoming widely accessible and embraced by everyday users. However, these models ha…
Classifier-Free Guidance inside the Attraction Basin May Cause Memorization
Anubhav Jain, Yuya Kobayashi, Takashi Shibuya +4
Diffusion models are prone to exactly reproduce images from the training data. This exact reproduction of the training data is concerning as it can lead to copyright infringement a…