Diffusion models and large language models have emerged as leading-edge generative
models and have sparked a revolutionary impact on various aspects of human life. However …

In recent years Text-to-Image (T2I) models have seen remarkable advancements gaining
widespread adoption. However this progress has inadvertently opened avenues for …

Diffusion models (DMs) have achieved state-of-the-art performance on various generative
tasks such as image synthesis, text-to-image, and text-guided image-to-image generation …

With the great achievement of vision transformers (ViTs), transformer-based approaches
have become the new paradigm for solving various computer vision tasks. However, recent …

Deep neural networks are vulnerable to adversarial examples, dictating the imperativeness
to test the model's robustness before deployment. Transfer-based attackers craft adversarial …

Adversarial examples for diffusion models are widely used as solutions for safety concerns.
By adding adversarial perturbations to personal images, attackers can not edit or imitate …

Imperceptibility is one of the crucial requirements for adversarial examples. Previous
adversarial attacks on 3D point cloud recognition suffer from noticeable outliers, resulting in …

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

The high-quality generation results of conditional diffusion models have brought about
concerns regarding privacy and copyright issues. As a possible technique for preventing the …

To address the problem of incomplete perception of limited viewpoints of ore blocks in future
remote and intelligent shoveling-dominated mining scenarios, a method of using new view …