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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

Current large-scale generative models have impressive efficiency in generating high-quality images based on text prompts. However, they lack the ability to precisely control the size and position of objects in the generated image. In this…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Jiafeng Mao , Xueting Wang

We introduce RealmDreamer, a technique for generating forward-facing 3D scenes from text descriptions. Our method optimizes a 3D Gaussian Splatting representation to match complex text prompts using pretrained diffusion models. Our key…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Jaidev Shriram , Alex Trevithick , Lingjie Liu , Ravi Ramamoorthi

Text-to-image generation models~(e.g., Stable Diffusion) have achieved significant advancements, enabling the creation of high-quality and realistic images based on textual descriptions. Prompt inversion, the task of identifying the textual…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Mingzhe Li , Kejing Xia , Gehao Zhang , Zhenting Wang , Guanhong Tao , Siqi Pan , Juan Zhai , Shiqing Ma

Diffusion models have demonstrated their effectiveness across various generative tasks. However, when applied to medical image segmentation, these models encounter several challenges, including significant resource and time requirements.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Lin , Zhiguang Chen , Zhonghao Yan , Weijiang Yu , Fudan Zheng

Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely edit the generated or real images. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

Text-to-image diffusion models sometimes depict blended concepts in the generated images. One promising use case of this effect would be the nonword-to-image generation task which attempts to generate images intuitively imaginable from a…

Multimedia · Computer Science 2024-11-07 Chihaya Matsuhira , Marc A. Kastner , Takahiro Komamizu , Takatsugu Hirayama , Ichiro Ide

Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely on a pretrained text-guided image-to-image generative model…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Pengcheng Xu , Qingnan Fan , Fei Kou , Shuai Qin , Hong Gu , Ruoyu Zhao , Charles Ling , Boyu Wang

Diffusion models are known for generating high-quality images, causing serious security concerns. To combat this, most efforts rely on deep neural networks (e.g., CNNs and Transformers), while largely overlooking the potential of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Mengxin Fu , Yuezun Li

We present DiffGaze, a novel method for generating realistic and diverse continuous human gaze sequences on 360{\deg} images based on a conditional score-based denoising diffusion model. Generating human gaze on 360{\deg} images is…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Chuhan Jiao , Yao Wang , Guanhua Zhang , Mihai Bâce , Zhiming Hu , Andreas Bulling

Text-guided diffusion models have revolutionized image generation and editing, offering exceptional realism and diversity. Specifically, in the context of diffusion-based editing, where a source image is edited according to a target prompt,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-20 Xuan Ju , Ailing Zeng , Yuxuan Bian , Shaoteng Liu , Qiang Xu

Latent diffusion models excel at producing high-quality images from text. Yet, concerns appear about the lack of diversity in the generated imagery. To tackle this, we introduce Diverse Diffusion, a method for boosting image diversity…

Computer Vision and Pattern Recognition · Computer Science 2023-10-20 Mariia Zameshina , Olivier Teytaud , Laurent Najman

Text-driven image generation using diffusion models has recently gained significant attention. To enable more flexible image manipulation and editing, recent research has expanded from single image generation to transparent layer generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Junjia Huang , Pengxiang Yan , Jinhang Cai , Jiyang Liu , Zhao Wang , Yitong Wang , Xinglong Wu , Guanbin Li

The landscape of image generation has been forever changed by open vocabulary diffusion models. However, at their core these models use transformers, which makes generation slow. Better implementations to increase the throughput of these…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Daniel Bolya , Judy Hoffman

Generative models have been widely studied in computer vision. Recently, diffusion models have drawn substantial attention due to the high quality of their generated images. A key desired property of image generative models is the ability…

Computer Vision and Pattern Recognition · Computer Science 2022-12-20 Qiucheng Wu , Yujian Liu , Handong Zhao , Ajinkya Kale , Trung Bui , Tong Yu , Zhe Lin , Yang Zhang , Shiyu Chang

Evaluating the quality of automatically generated image descriptions is a complex task that requires metrics capturing various dimensions, such as grammaticality, coverage, accuracy, and truthfulness. Although human evaluation provides…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Jia-Hong Huang , Hongyi Zhu , Yixian Shen , Stevan Rudinac , Evangelos Kanoulas

High resolution panoramic video content is paramount for immersive experiences in Virtual Reality, but is non-trivial to collect as it requires specialized equipment and intricate camera setups. In this work, we introduce VideoPanda, a…

High-resolution computed tomography (CT) imaging is essential for medical diagnosis but requires increased radiation exposure, creating a critical trade-off between image quality and patient safety. While deep learning methods have shown…

Image and Video Processing · Electrical Eng. & Systems 2025-06-16 Chunlei Li , Yilei Shi , Haoxi Hu , Jingliang Hu , Xiao Xiang Zhu , Lichao Mou

Recent text-to-image models have achieved impressive results in generating high-quality images. However, when tasked with multi-concept generation creating images that contain multiple characters or objects, existing methods often suffer…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Yang Zhang , Rui Zhang , Xuecheng Nie , Haochen Li , Jikun Chen , Yifan Hao , Xin Zhang , Luoqi Liu , Ling Li

The rapid advancement of Text-to-Image(T2I) generative models has enabled the synthesis of high-quality images guided by textual descriptions. Despite this significant progress, these models are often susceptible in generating contents that…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Yichen Sun , Zhixuan Chu , Zhan Qin , Kui Ren