According to numerous reports, ChatGPT represents a significant breakthrough in the field of
artificial intelligence. ChatGPT is a pre-trained AI model designed to engage in natural …

The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Vision transformers have shown great success due to their high model capabilities.
However, their remarkable performance is accompanied by heavy computation costs, which …

The most advanced text-to-image (T2I) models require significant training costs (eg, millions
of GPU hours), seriously hindering the fundamental innovation for the AIGC community …

The quadratic computation complexity of self-attention has been a persistent challenge
when applying Transformer models to vision tasks. Linear attention, on the other hand, offers …

Recent advances in deep learning have relied heavily on the use of large Transformers due
to their ability to learn at scale. However, the core building block of Transformers, the …

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 …

Image restoration involves recovering a high-quality clean image from its degraded version.
Deep learning-based methods have significantly improved image restoration performance …

Inspired by the long-range modeling ability of ViTs large-kernel convolutions are widely
studied and adopted recently to enlarge the receptive field and improve model performance …

Previous works have shown that increasing the window size for Transformer-based image
super-resolution models (eg, SwinIR) can significantly improve the model performance but …