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The Stable Diffusion Model (SDM) is a popular and efficient text-to-image (t2i) generation and image-to-image (i2i) generation model. Although there have been some attempts to reduce sampling steps, model distillation, and network…

Computer Vision and Pattern Recognition · Computer Science 2024-03-06 Jinchao Zhu , Yuxuan Wang , Xiaobing Tu , Siyuan Pan , Pengfei Wan , Gao Huang

The Stable Diffusion Model (SDM) is a prevalent and effective model for text-to-image (T2I) and image-to-image (I2I) generation. Despite various attempts at sampler optimization, model distillation, and network quantification, these…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Jinchao Zhu , Yuxuan Wang , Siyuan Pan , Pengfei Wan , Di Zhang , Gao Huang

The intensive computational burden of Stable Diffusion (SD) for text-to-image generation poses a significant hurdle for its practical application. To tackle this challenge, recent research focuses on methods to reduce sampling steps, such…

As text-to-image (T2I) synthesis models increase in size, they demand higher inference costs due to the need for more expensive GPUs with larger memory, which makes it challenging to reproduce these models in addition to the restricted…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Youngwan Lee , Kwanyong Park , Yoorhim Cho , Yong-Ju Lee , Sung Ju Hwang

As text-to-image models grow increasingly powerful and complex, their burgeoning size presents a significant obstacle to widespread adoption, especially on resource-constrained devices. This paper presents a pioneering study on…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Samarth N Ramesh , Zhixue Zhao

This paper presents SANA-Sprint, an efficient diffusion model for ultra-fast text-to-image (T2I) generation. SANA-Sprint is built on a pre-trained foundation model and augmented with hybrid distillation, dramatically reducing inference…

Graphics · Computer Science 2025-09-30 Junsong Chen , Shuchen Xue , Yuyang Zhao , Jincheng Yu , Sayak Paul , Junyu Chen , Han Cai , Song Han , Enze Xie

As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications have emerged. Despite the impressive results achieved by…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Geonung Kim , Beomsu Kim , Eunhyeok Park , Sunghyun Cho

Text-to-image generation via Stable Diffusion models (SDM) have demonstrated remarkable capabilities. However, their computational intensity, particularly in the iterative denoising process, hinders real-time deployment in latency-sensitive…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Shuaiting Li , Juncan Deng , Zeyu Wang , Kedong Xu , Rongtao Deng , Hong Gu , Haibin Shen , Kejie Huang

As scaling laws in generative AI push performance, they also simultaneously concentrate the development of these models among actors with large computational resources. With a focus on text-to-image (T2I) generative models, we aim to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Vikash Sehwag , Xianghao Kong , Jingtao Li , Michael Spranger , Lingjuan Lyu

Recently, the strong latent Diffusion Probabilistic Model (DPM) has been applied to high-quality Text-to-Image (T2I) generation (e.g., Stable Diffusion), by injecting the encoded target text prompt into the gradually denoised diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Mingyang Yi , Aoxue Li , Yi Xin , Zhenguo Li

Diffusion models (DMs) have demonstrated exceptional generative capabilities across various domains, including image, video, and so on. A key factor contributing to their effectiveness is the high quantity and quality of data used during…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Qianlong Xiang , Miao Zhang , Yuzhang Shang , Jianlong Wu , Yan Yan , Liqiang Nie

Stable Diffusion has achieved remarkable success in the field of text-to-image generation, with its powerful generative capabilities and diverse generation results making a lasting impact. However, its iterative denoising introduces high…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Evelyn Zhang , Bang Xiao , Jiayi Tang , Qianli Ma , Chang Zou , Xuefei Ning , Xuming Hu , Linfeng Zhang

This paper introduces a discrete diffusion model (DDM) framework for text-aligned speech tokenization and reconstruction. By replacing the auto-regressive speech decoder with a discrete diffusion counterpart, our model achieves…

Audio and Speech Processing · Electrical Eng. & Systems 2025-09-25 Pin-Jui Ku , He Huang , Jean-Marie Lemercier , Subham Sekhar Sahoo , Zhehuai Chen , Ante Jukić

The Diffusion Model (DM) has emerged as the SOTA approach for image synthesis. However, the existing DM cannot perform well on some image-to-image translation (I2I) tasks. Different from image synthesis, some I2I tasks, such as…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Bin Xia , Yulun Zhang , Shiyin Wang , Yitong Wang , Xinglong Wu , Yapeng Tian , Wenming Yang , Radu Timotfe , Luc Van Gool

Diffusion Models~(DMs) have emerged as the dominant approach in Generative Artificial Intelligence (GenAI), owing to their remarkable performance in tasks such as text-to-image synthesis. However, practical DMs, such as stable diffusion,…

Machine Learning · Computer Science 2025-08-18 Xuhui Fan , Zhangkai Wu , Hongyu Wu

Text-to-image diffusion models (T2I DMs), represented by Stable Diffusion, which generate highly realistic images based on textual input, have been widely used, but their flexibility also makes them prone to misuse for producing harmful or…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Chaoshuo Zhang , Chenhao Lin , Zhengyu Zhao , Le Yang , Qian Wang , Chao Shen

Despite their ability to generate high-resolution and diverse images from text prompts, text-to-image diffusion models often suffer from slow iterative sampling processes. Model distillation is one of the most effective directions to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Thuan Hoang Nguyen , Anh Tran

Text-to-image (T2I) generation using diffusion models has become a blockbuster service in today's AI cloud. A production T2I service typically involves a serving workflow where a base diffusion model is augmented with various "add-on"…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-09 Suyi Li , Lingyun Yang , Xiaoxiao Jiang , Hanfeng Lu , Dakai An , Zhipeng Di , Weiyi Lu , Jiawei Chen , Kan Liu , Yinghao Yu , Tao Lan , Guodong Yang , Lin Qu , Liping Zhang , Wei Wang

Text-to-image diffusion models can create stunning images from natural language descriptions that rival the work of professional artists and photographers. However, these models are large, with complex network architectures and tens of…

Computer Vision and Pattern Recognition · Computer Science 2023-10-17 Yanyu Li , Huan Wang , Qing Jin , Ju Hu , Pavlo Chemerys , Yun Fu , Yanzhi Wang , Sergey Tulyakov , Jian Ren

Large-scale, pre-trained Text-to-Image (T2I) diffusion models have gained significant popularity in image generation tasks and have shown unexpected potential in image Super-Resolution (SR). However, most existing T2I diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Brian B. Moser , Stanislav Frolov , Tobias C. Nauen , Federico Raue , Andreas Dengel
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