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Related papers: State of the Art on Diffusion Models for Visual Co…

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The integration of generative AI in visual art has revolutionized not only how visual content is created but also how AI interacts with and reflects the underlying domain knowledge. This survey explores the emerging realm of diffusion-based…

Artificial Intelligence · Computer Science 2024-08-23 Bingyuan Wang , Qifeng Chen , Zeyu Wang

Diffusion models, a powerful and universal generative AI technology, have achieved tremendous success in computer vision, audio, reinforcement learning, and computational biology. In these applications, diffusion models provide flexible…

Machine Learning · Computer Science 2024-04-12 Minshuo Chen , Song Mei , Jianqing Fan , Mengdi Wang

Generative AI models have revolutionized various fields by enabling the creation of realistic and diverse data samples. Among these models, diffusion models have emerged as a powerful approach for generating high-quality images, text, and…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Gaurav Raut , Apoorv Singh

Generative artificial intelligence (AI) refers to algorithms that create synthetic but realistic output. Diffusion models currently offer state of the art performance in generative AI for images. They also form a key component in more…

Machine Learning · Computer Science 2023-12-27 Catherine F. Higham , Desmond J. Higham , Peter Grindrod

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 their impressive generative capabilities, diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Zhen Xing , Qijun Feng , Haoran Chen , Qi Dai , Han Hu , Hang Xu , Zuxuan Wu , Yu-Gang Jiang

Cross-Modal learning tasks have picked up pace in recent times. With plethora of applications in diverse areas, generation of novel content using multiple modalities of data has remained a challenging problem. To address the same, various…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Nikhil Verma

This pictorial presents an ongoing research programme comprising three practice-based Design Research projects conducted through 2024, exploring the affordances of diffusion-based AI image generation systems, specifically Stable Diffusion.…

Human-Computer Interaction · Computer Science 2024-11-21 Joseph Lindley , Roger Whitham

Diffusion and flow-based models have become the state of the art for generative AI across a wide range of data modalities, including images, videos, shapes, molecules, music, and more. This tutorial provides a self-contained introduction to…

Machine Learning · Computer Science 2026-03-19 Peter Holderrieth , Ezra Erives

The astonishing growth of generative tools in recent years has empowered many exciting applications in text-to-image generation and text-to-video generation. The underlying principle behind these generative tools is the concept of…

Machine Learning · Computer Science 2025-01-09 Stanley H. Chan

With the global population increasing and arable land resources becoming increasingly limited, smart and precision agriculture have emerged as essential directions for sustainable agricultural development. Artificial intelligence (AI),…

Machine Learning · Computer Science 2025-10-15 Xing Hu , Haodong Chen , Qianqian Duan , Dawei Zhang

The latest developments in Artificial Intelligence include diffusion generative models, quite popular tools which can produce original images both unconditionally and, in some cases, conditioned by some inputs provided by the user. Apart…

Computer Vision and Pattern Recognition · Computer Science 2023-02-13 Stefano Scotta , Alberto Messina

Diffusion-based generative models' impressive ability to create convincing images has garnered global attention. However, their complex internal structures and operations often pose challenges for non-experts to grasp. We introduce…

Human-Computer Interaction · Computer Science 2024-04-26 Seongmin Lee , Benjamin Hoover , Hendrik Strobelt , Zijie J. Wang , ShengYun Peng , Austin Wright , Kevin Li , Haekyu Park , Haoyang Yang , Polo Chau

In recent years, 3D vision has become a crucial field within computer vision, powering a wide range of applications such as autonomous driving, robotics, augmented reality, and medical imaging. This field relies on accurate perception,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Zhen Wang , Dongyuan Li , Yaozu Wu , Tianyu He , Jiang Bian , Renhe Jiang

Modern diffusion models have set the state-of-the-art in AI image generation. Their success is due, in part, to training on Internet-scale data which often includes copyrighted work. This prompts questions about the extent to which these…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Stephen Casper , Zifan Guo , Shreya Mogulothu , Zachary Marinov , Chinmay Deshpande , Rui-Jie Yew , Zheng Dai , Dylan Hadfield-Menell

Latent space is one of the key concepts in generative AI, offering powerful means for creative exploration through vector manipulation. However, diffusion models like Stable Diffusion lack the intuitive latent vector control found in GANs,…

Machine Learning · Computer Science 2025-09-29 Zhihua Zhong , Xuanyang Huang

Diffusion models have become a new SOTA generative modeling method in various fields, for which there are multiple survey works that provide an overall survey. With the number of articles on diffusion models increasing exponentially in the…

Machine Learning · Computer Science 2023-04-05 Mengchun Zhang , Maryam Qamar , Taegoo Kang , Yuna Jung , Chenshuang Zhang , Sung-Ho Bae , Chaoning Zhang

Diffusion models have emerged as a powerful new family of deep generative models with record-breaking performance in many applications, including image synthesis, video generation, and molecule design. In this survey, we provide an overview…

Machine Learning · Computer Science 2025-09-30 Ling Yang , Zhilong Zhang , Yang Song , Shenda Hong , Runsheng Xu , Yue Zhao , Wentao Zhang , Bin Cui , Ming-Hsuan Yang

Generative AI offers new opportunities for automating urban planning by creating site-specific urban layouts and enabling flexible design exploration. However, existing approaches often struggle to produce realistic and practical designs at…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Qingyi Wang , Yuebing Liang , Yunhan Zheng , Kaiyuan Xu , Jinhua Zhao , Shenhao Wang

Deep generative models have unlocked another profound realm of human creativity. By capturing and generalizing patterns within data, we have entered the epoch of all-encompassing Artificial Intelligence for General Creativity (AIGC).…

Artificial Intelligence · Computer Science 2023-12-27 Hanqun Cao , Cheng Tan , Zhangyang Gao , Yilun Xu , Guangyong Chen , Pheng-Ann Heng , Stan Z. Li

Image generation using generative AI is rapidly becoming a major new source of visual media, with billions of AI generated images created using diffusion models such as Stable Diffusion and Midjourney over the last few years. In this paper…

Human-Computer Interaction · Computer Science 2024-01-29 Jon McCormack , Maria Teresa Llano , Stephen James Krol , Nina Rajcic
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