While super-resolution (SR) methods based on diffusion models exhibit promising results
their practical application is hindered by the substantial number of required inference steps …

The potential for higher-resolution image generation using pretrained diffusion models is
immense, yet these models often struggle with issues of object repetition and structural …

Recent progress in generative diffusion models has greatly advanced text-to-video
generation. While text-to-video models trained on large-scale, diverse datasets can produce …

With the recent advancement in large language models (LLMs), there is a growing interest in
combining LLMs with multimodal learning. Previous surveys of multimodal large language …

Large-scale generative models, such as text-to-image diffusion models, have garnered
widespread attention across diverse domains due to their creative and high-fidelity image …

Diffusion models have emerged as frontrunners in text-to-image generation, however, their
fixed image resolution during training often leads to challenges in high-resolution image …

Wildfires are a significant threat to ecosystems and human infrastructure, leading to
widespread destruction and environmental degradation. Recent advancements in deep …

Wildfires are a significant threat to ecosystems and human infrastructure, leading to
widespread destruction and environmental degradation. Recent advancements in deep …

In this work, we introduce Pixelsmith, a zero-shot text-to-image generative framework to
sample images at higher resolutions with a single GPU. We are the first to show that it is …

Super-resolution methods are increasingly being specialized for both real-world and face-
specific tasks. However, many existing approaches rely on simplistic degradation models …