Generative AI has witnessed rapid advancement in recent years, expanding their
capabilities to create synthesized content such as text, images, audio, and code. The high …

In the evolving landscape of text-to-image (T2I) diffusion models, the remarkable capability
to generate high-quality images from textual descriptions faces challenges with the potential …

Abstract Text-to-image (T2I) diffusion models notably the unCLIP models (eg DALL-E-2)
achieve state-of-the-art (SOTA) performance on various compositional T2I benchmarks at …

Multimodal learning has been a field of increasing interest, aiming to combine various
modalities in a single joint representation. Especially in the area of visiolinguistic (VL) …

We propose a novel multi-bit box-free watermarking method for the protection of Intellectual
Property Rights (IPR) of GANs with improved robustness against white-box model-level …

Recent advancements in deep learning-based generative models have simplified image
generation, increasing the need for improved source tracing and copyright protection …

Watermarking is crucial for protecting the copyright of AI-generated images. We propose
WMAdapter, a diffusion model watermark plugin that takes user-specified watermark …

Despite the recent advances in personalized text-to-image (P-T2I) generative models,
subject-driven T2I remains challenging. The primary bottlenecks include 1) Intensive training …

Safeguarding intellectual property and preventing potential misuse of AI-generated images
are of paramount importance. This paper introduces a robust and agile plug-and-play …

Deep generative models have demonstrated impressive performance in various computer
vision applications, including image synthesis, video generation, and medical analysis …