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Artificial Intelligence-Generated Content (AIGC) has made significant strides, with high-resolution text-to-image (T2I) generation becoming increasingly critical for improving users' Quality of Experience (QoE). Although…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Chongbin Yi , Yuxin Liang , Ziqi Zhou , Peng Yang

Personalized text-to-image (P-T2I) generation aims to create new, text-guided images featuring the personalized subject with a few reference images. However, balancing the trade-off relationship between prompt fidelity and identity…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Kangyeol Kim , Wooseok Seo , Sehyun Nam , Bodam Kim , Suhyeon Jeong , Wonwoo Cho , Jaegul Choo , Youngjae Yu

Image-to-Video generation (I2V) animates a static image into a temporally coherent video sequence following textual instructions, yet preserving fine-grained object identity under changing viewpoints remains a persistent challenge. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Mingyang Wu , Ashirbad Mishra , Soumik Dey , Shuo Xing , Naveen Ravipati , Hansi Wu , Binbin Li , Zhengzhong Tu

Large-scale diffusion-based generative models have led to breakthroughs in text-conditioned high-resolution image synthesis. Starting from random noise, such text-to-image diffusion models gradually synthesize images in an iterative fashion…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Yogesh Balaji , Seungjun Nah , Xun Huang , Arash Vahdat , Jiaming Song , Qinsheng Zhang , Karsten Kreis , Miika Aittala , Timo Aila , Samuli Laine , Bryan Catanzaro , Tero Karras , Ming-Yu Liu

Advanced diffusion-based Text-to-Image (T2I) models, such as the Stable Diffusion Model, have made significant progress in generating diverse and high-quality images using text prompts alone. However, when non-famous users require…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Yang Li , Songlin Yang , Wei Wang , Jing Dong

Identity-preserving text-to-video (IPT2V) generation aims to create high-fidelity videos with consistent human identity. It is an important task in video generation but remains an open problem for generative models. This paper pushes the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Shenghai Yuan , Jinfa Huang , Xianyi He , Yunyuan Ge , Yujun Shi , Liuhan Chen , Jiebo Luo , Li Yuan

Text-to-image (T2I) models have achieved remarkable progress, yet they continue to struggle with complex prompts that require simultaneously handling multiple objects, relations, and attributes. Existing inference-time strategies, such as…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Shantanu Jaiswal , Mihir Prabhudesai , Nikash Bhardwaj , Zheyang Qin , Amir Zadeh , Chuan Li , Katerina Fragkiadaki , Deepak Pathak

Text-to-image models offer a new level of creative flexibility by allowing users to guide the image generation process through natural language. However, using these models to consistently portray the same subject across diverse prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Yoad Tewel , Omri Kaduri , Rinon Gal , Yoni Kasten , Lior Wolf , Gal Chechik , Yuval Atzmon

Text-to-Image (T2I) generation has long been an open problem, with compositional synthesis remaining particularly challenging. This task requires accurate rendering of complex scenes containing multiple objects that exhibit diverse…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Shijian Wang , Runhao Fu , Siyi Zhao , Qingqin Zhan , Xingjian Wang , Jiarui Jin , Yuan Lu , Hanqian Wu , Cunjian Chen

One challenge in text-to-image (T2I) generation is the inadvertent reflection of culture gaps present in the training data, which signifies the disparity in generated image quality when the cultural elements of the input text are rarely…

Computer Vision and Pattern Recognition · Computer Science 2023-07-07 Bingshuai Liu , Longyue Wang , Chenyang Lyu , Yong Zhang , Jinsong Su , Shuming Shi , Zhaopeng Tu

We present Infinite-Story, a training-free framework for consistent text-to-image (T2I) generation tailored for multi-prompt storytelling scenarios. Built upon a scale-wise autoregressive model, our method addresses two key challenges in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Jihun Park , Kyoungmin Lee , Jongmin Gim , Hyeonseo Jo , Minseok Oh , Wonhyeok Choi , Kyumin Hwang , Jaeyeul Kim , Minwoo Choi , Sunghoon Im

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

Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements for storytelling. Existing approaches to this problem…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Tao Liu , Kai Wang , Senmao Li , Joost van de Weijer , Fahad Shahbaz Khan , Shiqi Yang , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Text-to-image (T2I) models have significantly advanced the development of artificial intelligence, enabling the generation of high-quality images in diverse contexts based on specific text prompts. However, existing T2I-based methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Salaheldin Mohamed , Dong Han , Yong Li

Text-to-image (T2I) diffusion models have revolutionized generative modeling by producing high-fidelity, diverse, and visually realistic images from textual prompts. Despite these advances, existing models struggle with complex prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Eric Hanchen Jiang , Yasi Zhang , Zhi Zhang , Yixin Wan , Andrew Lizarraga , Shufan Li , Ying Nian Wu

Despite astonishing progress, generating realistic images of complex scenes remains a challenging problem. Recently, layout-to-image synthesis approaches have attracted much interest by conditioning the generator on a list of bounding boxes…

Computer Vision and Pattern Recognition · Computer Science 2022-04-06 Stanislav Frolov , Prateek Bansal , Jörn Hees , Andreas Dengel

Diffusion-driven text-to-image (T2I) generation has achieved remarkable advancements in recent years. To further improve T2I models' capability in numerical and spatial reasoning, layout is employed as an intermedium to bridge large…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Yuhao Jia , Wenhan Tan

The surge in the popularity of text-to-image generators (T2Is) has been matched by extensive research into ensuring fairness and equitable outcomes, with a focus on how they impact society. However, such work has typically focused on…

Computers and Society · Computer Science 2024-08-06 Sourojit Ghosh

Controllable text-to-image (T2I) diffusion models have shown impressive performance in generating high-quality visual content through the incorporation of various conditions. Current methods, however, exhibit limited performance when guided…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Jiajun Wang , Morteza Ghahremani , Yitong Li , Björn Ommer , Christian Wachinger

In this paper, we revisit the Image-to-Image (I2I) translation problem with transition consistency, namely the consistency defined on the conditional data mapping between each data pairs. Explicitly parameterizing each data mappings with a…

Computer Vision and Pattern Recognition · Computer Science 2021-03-10 Yaxin Shi , Xiaowei Zhou , Ping Liu , Ivor Tsang