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Related papers: CoDi: Subject-Consistent and Pose-Diverse Text-to-…

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Text-to-Image (T2I) diffusion models have demonstrated strong generation ability, but their potential to generate unsafe content raises significant safety concerns. Existing inference-time defense methods typically perform category-agnostic…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Binhong Tan , Zhaoxin Wang , Handing Wang

Recently, significant advancements have been made in 3D generative models, however training these models across diverse domains is challenging and requires an huge amount of training data and knowledge of pose distribution. Text-guided…

Computer Vision and Pattern Recognition · Computer Science 2023-04-05 Gwanghyun Kim , Ji Ha Jang , Se Young Chun

Impressive advances in text-to-image (T2I) generative models have yielded a plethora of high performing models which are able to generate aesthetically appealing, photorealistic images. Despite the progress, these models still struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Oscar Mañas , Pietro Astolfi , Melissa Hall , Candace Ross , Jack Urbanek , Adina Williams , Aishwarya Agrawal , Adriana Romero-Soriano , Michal Drozdzal

Text-to-Image (T2I) generation is enabling new applications that support creators, designers, and general end users of productivity software by generating illustrative content with high photorealism starting from a given descriptive text as…

Computers and Society · Computer Science 2023-04-14 Ranjita Naik , Besmira Nushi

Diffusion models have attracted significant attention due to the remarkable ability to create content and generate data for tasks like image classification. However, the usage of diffusion models to generate the high-quality object…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Kai Chen , Enze Xie , Zhe Chen , Yibo Wang , Lanqing Hong , Zhenguo Li , Dit-Yan Yeung

When humans read a specific text, they often visualize the corresponding images, and we hope that computers can do the same. Text-to-image synthesis (T2I), which focuses on generating high-quality images from textual descriptions, has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Nonghai Zhang , Hao Tang

Due to the demand for personalizing image generation, subject-driven text-to-image generation method, which creates novel renditions of an input subject based on text prompts, has received growing research interest. Existing methods often…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Shang Chai , Zihang Lin , Min Zhou , Xubin Li , Liansheng Zhuang , Houqiang Li

We propose a diffusion-based approach for Text-to-Image (T2I) generation with interactive 3D layout control. Layout control has been widely studied to alleviate the shortcomings of T2I diffusion models in understanding objects' placement…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Abdelrahman Eldesokey , Peter Wonka

Despite advancements in text-to-image generation (T2I), prior methods often face text-image misalignment problems such as relation confusion in generated images. Existing solutions involve cross-attention manipulation for better…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Leigang Qu , Wenjie Wang , Yongqi Li , Hanwang Zhang , Liqiang Nie , Tat-Seng Chua

Recently, the introduction of Chain-of-Thought (CoT) has largely improved the generation ability of unified models. However, it is observed that the current thinking process during generation mainly focuses on the text consistency with the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Zixuan Ye , Quande Liu , Cong Wei , Yuanxing Zhang , Xintao Wang , Pengfei Wan , Kun Gai , Wenhan Luo

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

Recent advancements in large language models have demonstrated how chain-of-thought (CoT) and reinforcement learning (RL) can improve performance. However, applying such reasoning strategies to the visual generation domain remains largely…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Dongzhi Jiang , Ziyu Guo , Renrui Zhang , Zhuofan Zong , Hao Li , Le Zhuo , Shilin Yan , Pheng-Ann Heng , Hongsheng Li

Text-to-Image (T2I) generation methods based on diffusion model have garnered significant attention in the last few years. Although these image synthesis methods produce visually appealing results, they frequently exhibit spelling errors…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yiming Zhao , Zhouhui Lian

Despite recent progress, text-to-image models still struggle to generate semantically diverse and compositionally accurate multi-person interaction scenes, often collapsing to repetitive layouts, stereotypical poses, and poorly grounded…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Wenxuan Peng , Bharath Hariharan , Hadar Averbuch-Elor

In this project, we address the issue of infidelity in text-to-image generation, particularly for actions involving multiple objects. For this we build on top of the CONFORM framework which uses Contrastive Learning to improve the accuracy…

Computer Vision and Pattern Recognition · Computer Science 2025-01-17 Tianxiang Xia , Lin Xiao , Yannick Montorfani , Francesco Pavia , Enis Simsar , Thomas Hofmann

We present Composable Diffusion (CoDi), a novel generative model capable of generating any combination of output modalities, such as language, image, video, or audio, from any combination of input modalities. Unlike existing generative AI…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Zineng Tang , Ziyi Yang , Chenguang Zhu , Michael Zeng , Mohit Bansal

High-resolution image-to-video (I2V) generation aims to synthesize realistic temporal dynamics while preserving fine-grained appearance details of the input image. At 2K resolution, it becomes extremely challenging, and existing solutions…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 YaoYang Liu , Yuechen Zhang , Wenbo Li , Yufei Zhao , Rui Liu , Long Chen

Generating text-editable and pose-controllable character videos have an imperious demand in creating various digital human. Nevertheless, this task has been restricted by the absence of a comprehensive dataset featuring paired video-pose…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Yue Ma , Yingqing He , Xiaodong Cun , Xintao Wang , Siran Chen , Ying Shan , Xiu Li , Qifeng Chen

Recent advancements in text-to-image generation models have dramatically enhanced the generation of photorealistic images from textual prompts, leading to an increased interest in personalized text-to-image applications, particularly in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Xierui Wang , Siming Fu , Qihan Huang , Wanggui He , Hao Jiang

Text-to-image (T2I) systems enable rapid generation of high-fidelity imagery but are misaligned with how visual ideas develop. T2I systems generate outputs that make implicit visual decisions on behalf of the user, often introduce…

Human-Computer Interaction · Computer Science 2026-04-16 Zoe De Simone , Angie Boggust , Fredo Durand , Ashia Wilson , Arvind Satyanarayan
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