In this paper, we introduce PixArt-Σ, a Diffusion Transformer model (DiT) capable of directly
generating images at 4K resolution. PixArt-Σ represents a significant advancement over its …

We present Lumina-mGPT, a family of multimodal autoregressive models capable of various
vision and language tasks, particularly excelling in generating flexible photorealistic images …

Diffusion models have proven to be highly effective in image and video generation;
however, they encounter challenges in the correct composition of objects when generating …

In this study, we delve into the generation of high-resolution images from pre-trained
diffusion models, addressing persistent challenges, such as repetitive patterns and structural …

This paper attempts to address the object repetition issue in patch-wise higher-resolution
image generation. We propose AccDiffusion, an accurate method for patch-wise higher …

Modern diffusion models, particularly those utilizing a Transformer-based UNet for
denoising, rely heavily on self-attention operations to manage complex spatial relationships …

Diffusion models have shown remarkable performance in image generation in recent years.
However, due to a quadratic increase in memory during generating ultra-high-resolution …

Creating multi-view wire art (MVWA) a static 3D sculpture with diverse interpretations from
different viewpoints is a complex task even for skilled artists. In response we present …

The emergence of text-to-image generation models has led to the recognition that image
enhancement, performed as post-processing, would significantly improve the visual quality …

This paper propels creative control in generative visual AI by allowing users to “select”.
Departing from traditional text or sketch-based methods, we for the first time allow users to …