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Despite the recent advances in large-scale diffusion models, little progress has been made on the layout-to-image (L2I) synthesis task. Current L2I models either suffer from poor editability via text or weak alignment between the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Yumeng Li , Margret Keuper , Dan Zhang , Anna Khoreva

Text-to-image (T2I) diffusion models have drawn attention for their ability to generate high-quality images with precise text alignment. However, these models can also be misused to produce inappropriate content. Existing safety measures,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Hongxiang Zhang , Yifeng He , Hao Chen

Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. However, the effective integration of T2I models into…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Zhicai Wang , Longhui Wei , Tan Wang , Heyu Chen , Yanbin Hao , Xiang Wang , Xiangnan He , Qi Tian

Text-to-image diffusion models (T2I DMs) have achieved remarkable success in generating high-quality and diverse images from text prompts, yet recent studies have revealed their vulnerability to backdoor attacks. Existing attack methods…

Cryptography and Security · Computer Science 2025-08-05 Haoran Dai , Jiawen Wang , Ruo Yang , Manali Sharma , Zhonghao Liao , Yuan Hong , Binghui Wang

Layout generation is a foundation task of graphic design, which requires the integration of visual aesthetics and harmonious expression of content delivery. However, existing methods still face challenges in generating precise and visually…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Yu Li , Yifan Chen , Gongye Liu , Fei Yin , Qingyan Bai , Jie Wu , Hongfa Wang , Ruihang Chu , Yujiu Yang

Zero-shot object counting aims to count instances of arbitrary object categories specified by text descriptions. Existing methods typically rely on vision-language models like CLIP, but often exhibit limited sensitivity to text prompts. We…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Yifei Qian , Zhongliang Guo , Bowen Deng , Chun Tong Lei , Shuai Zhao , Chun Pong Lau , Xiaopeng Hong , Michael P. Pound

Text-to-image (T2I) generative models, such as Stable Diffusion and DALL-E, have shown remarkable proficiency in producing high-quality, realistic, and natural images from textual descriptions. However, these models sometimes fail to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Arash Marioriyad , Parham Rezaei , Mahdieh Soleymani Baghshah , Mohammad Hossein Rohban

With the advent of diffusion models, Text-to-Image (T2I) generation has seen substantial advancements. Current T2I models allow users to specify object colors using linguistic color names, and some methods aim to personalize color-object…

Graphics · Computer Science 2025-08-13 Qianru Qiu , Jiafeng Mao , Xueting Wang

The diffusion model has provided a strong tool for implementing text-to-image (T2I) and image-to-image (I2I) generation. Recently, topology and texture control are popular explorations, e.g., ControlNet, IP-Adapter, Ctrl-X, and DSG. These…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Jia Li , Nan Gao , Huaibo Huang , Ran He

Recent breakthroughs of transformer-based diffusion models, particularly with Multimodal Diffusion Transformers (MMDiT) driven models like FLUX and Qwen Image, have facilitated thrilling experiences in text-to-image generation and editing.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Binglei Li , Mengping Yang , Zhiyu Tan , Junping Zhang , Hao Li

The text-to-image (T2I) personalization diffusion model can generate images of the novel concept based on the user input text caption. However, existing T2I personalized methods either require test-time fine-tuning or fail to generate…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Xiao Guo , Manh Tran , Jiaxin Cheng , Xiaoming Liu

Recent advances in diffusion models have enabled high-quality generation and manipulation of images guided by texts, as well as concept learning from images. However, naive applications of existing methods to editing tasks that require…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xudong Liu , Zikun Chen , Ruowei Jiang , Ziyi Wu , Kejia Yin , Han Zhao , Parham Aarabi , Igor Gilitschenski

Recent advancements in Virtual Try-On (VTO) have demonstrated exceptional efficacy in generating realistic images and preserving garment details, largely attributed to the robust generative capabilities of text-to-image (T2I) diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhenchen Wan , Yanwu Xu , Zhaoqing Wang , Feng Liu , Tongliang Liu , Mingming Gong

The issue of generative pretraining for vision models has persisted as a long-standing conundrum. At present, the text-to-image (T2I) diffusion model demonstrates remarkable proficiency in generating high-definition images matching textual…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Qiang Wan , Zilong Huang , Bingyi Kang , Jiashi Feng , Li Zhang

Modern Latent Diffusion Models (LDMs) typically operate in low-level Variational Autoencoder (VAE) latent spaces that are primarily optimized for pixel-level reconstruction. To unify vision generation and understanding, a burgeoning trend…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Shilong Zhang , He Zhang , Zhifei Zhang , Chongjian Ge , Shuchen Xue , Shaoteng Liu , Mengwei Ren , Soo Ye Kim , Yuqian Zhou , Qing Liu , Daniil Pakhomov , Kai Zhang , Zhe Lin , Ping Luo

Continual post-training adapts a single text-to-image diffusion model to learn new tasks without incurring the cost of separate models, but naive post-training causes forgetting of pretrained knowledge and undermines zero-shot…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Zhehao Huang , Yuhang Liu , Yixin Lou , Zhengbao He , Mingzhen He , Wenxing Zhou , Tao Li , Kehan Li , Zeyi Huang , Xiaolin Huang

Text-to-image (T2I) generation using multiple conditions enables fine-grained user control on the generated image. Yet, incorporating multi-condition inputs incurs substantial computation and communication overhead, due to additional…

Multimedia · Computer Science 2026-05-12 Yuxin Kong , Peng Yang , Chongbin Yi , Fan Wu , Feng Lyu

Recent progress in text-to-image (T2I) models enables high-quality image generation with flexible textual control. To utilize the abundant visual priors in the off-the-shelf T2I models, a series of methods try to invert an image to proper…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Zijie Wu , Chaohui Yu , Zhen Zhu , Fan Wang , Xiang Bai

Large text-to-image models achieved a remarkable leap in the evolution of AI, enabling high-quality and diverse synthesis of images from a given text prompt. However, these models lack the ability to mimic the appearance of subjects in a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Nataniel Ruiz , Yuanzhen Li , Varun Jampani , Yael Pritch , Michael Rubinstein , Kfir Aberman

Creating editable videos that depict complex interactions between multiple objects in various artistic styles has long been a challenging task in filmmaking. Progress is often hampered by the scarcity of data sets that contain paired text…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Anisha Jain
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