3 papers
cs.CV2025
Dark Miner: Defend against undesirable generation for text-to-image diffusion models
Zheling Meng, Bo Peng, Xiaochuan Jin +4
Text-to-image diffusion models have been demonstrated with undesired generation due to unfiltered large-scale training data, such as sexual images and copyrights, necessitating the…
cs.CV2025
Concept Corrector: Erase concepts on the fly for text-to-image diffusion models
Zheling Meng, Bo Peng, Xiaochuan Jin +4
Text-to-image diffusion models have demonstrated the underlying risk of generating various unwanted content, such as sexual elements. To address this issue, the task of concept era…
cs.CV2024
Latent Watermark: Inject and Detect Watermarks in Latent Diffusion Space
Zheling Meng, Bo Peng, Jing Dong
Watermarking is a tool for actively identifying and attributing the images generated by latent diffusion models. Existing methods face the dilemma of image quality and watermark ro…