The recent wave of AI-generated content (AIGC) has witnessed substantial success in
computer vision, with the diffusion model playing a crucial role in this achievement. Due to …

The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

The diffusion-based generative models have achieved remarkable success in text-based
image generation. However, since it contains enormous randomness in generation …

This work aims to learn a high-quality text-to-video (T2V) generative model by leveraging a
pre-trained text-to-image (T2I) model as a basis. It is a highly desirable yet challenging task …

Large-scale text-to-image generative models have shown their remarkable ability to
synthesize diverse, high-quality images. However, directly applying these models for real …

In addition to the unprecedented ability in imaginary creation, large text-to-image models are
expected to take customized concepts in image generation. Existing works generally learn …

We present DreamBooth3D, an approach to personalize text-to-3D generative models from
as few as 3-6 casually captured images of a subject. Our approach combines recent …

Image diffusion models, trained on massive image collections, have emerged as the most
versatile image generator model in terms of quality and diversity. They support inverting real …

Recently, diffusion models have achieved remarkable success in text-to-image generation,
enabling the creation of high-quality images from text prompts and various conditions …

Large-scale generative models are capable of producing high-quality images from detailed
prompts. However, many aspects of an image are difficult or impossible to convey through …