Recent advancements in text-to-image generation driven by diffusion models have sparked interest in text-guided 3D generation, aiming to automate 3D asset creation for virtual reality, movies, and gaming. However, challenges arise in 3D synthesis due to scarce high-quality data and the complexity of generative modeling with 3D representations. Score distillation techniques have emerged to address…

Adversarial attacks in image classification, a critical issue in AI security, involve subtle changes to images that mislead AI models into incorrect classifications. The research delves into the intricacies of these attacks, particularly focusing on multi-attacks, where a single alteration can simultaneously affect multiple images’ classifications. This phenomenon is not just a theoretical concern but…

Artificial intelligence has always faced the issue of producing high-quality videos that smoothly integrate multimodal inputs like text and graphics. Text-to-video generation techniques now in use frequently concentrate on single-modal conditioning, using either text or images alone. The accuracy and control researchers can exert over the created films are limited by this unimodal technique, making…

Diffusion models are a significant component in generative models, particularly for image generation, and these models are undergoing transformative advancements. These models, functioning by transforming noise into structured data, especially images, through a denoising process, have become increasingly important in computer vision and related fields. Their capability to convert pure noise into detailed images has…