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Gestures perform a variety of communicative functions that powerfully influence human face-to-face interaction. How this communicative function is achieved varies greatly between individuals and depends on the role of the speaker and the…

Human-Computer Interaction · Computer Science 2023-10-24 Laura B. Hensel , Nutchanon Yongsatianchot , Parisa Torshizi , Elena Minucci , Stacy Marsella

Personalized text-to-image generation has attracted unprecedented attention in the recent few years due to its unique capability of generating highly-personalized images via using the input concept dataset and novel textual prompt. However,…

Artificial Intelligence · Computer Science 2024-07-02 Shian Du , Xiaotian Cheng , Qi Qian , Henglu Wei , Yi Xu , Xiangyang Ji

Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex prompts, such as those that involve numeracy and spatial…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Long Lian , Boyi Li , Adam Yala , Trevor Darrell

Text-to-image generation models have seen considerable advancement, catering to the increasing interest in personalized image creation. Current customization techniques often necessitate users to provide multiple images (typically 3-5) for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Linhao Zhong , Yan Hong , Wentao Chen , Binglin Zhou , Yiyi Zhang , Jianfu Zhang , Liqing Zhang

Text-to-Image (T2I) models have made remarkable progress in generating images from text prompts, but their output quality and safety still depend heavily on how prompts are phrased. Existing safety methods typically refine prompts using…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Jinwoo Jeon , JunHyeok Oh , Hayeong Lee , Byung-Jun Lee

Text animation, a foundational element in video creation, enables efficient and cost-effective communication, thriving in advertisements, journalism, and social media. However, traditional animation workflows present significant usability…

Human-Computer Interaction · Computer Science 2025-06-13 Bao Zhang , Zihan Li , Zhenglei Liu , Huanchen Wang , Yuxin Ma

This study examines how Large Language Models (LLMs) can reduce biases in text-to-image generation systems by modifying user prompts. We define bias as a model's unfair deviation from population statistics given neutral prompts. Our…

Computation and Language · Computer Science 2025-04-16 René Peinl

The text-to-image synthesis by diffusion models has recently shown remarkable performance in generating high-quality images. Although performs well for simple texts, the models may get confused when faced with complex texts that contain…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Chang Yu , Junran Peng , Xiangyu Zhu , Zhaoxiang Zhang , Qi Tian , Zhen Lei

Fashion content generation is an emerging area at the intersection of artificial intelligence and creative design, with applications ranging from virtual try-on to culturally diverse design prototyping. Existing methods often struggle with…

Computation and Language · Computer Science 2025-01-28 Spencer Ramsey , Amina Grant , Jeffrey Lee

Product review generation is an important task in recommender systems, which could provide explanation and persuasiveness for the recommendation. Recently, Large Language Models (LLMs, e.g., ChatGPT) have shown superior text modeling and…

Computation and Language · Computer Science 2024-07-11 Qiyao Peng , Hongtao Liu , Hongyan Xu , Qing Yang , Minglai Shao , Wenjun Wang

Despite impressive recent advances in text-to-image diffusion models, obtaining high-quality images often requires prompt engineering by humans who have developed expertise in using them. In this work, we present NeuroPrompts, an adaptive…

Artificial Intelligence · Computer Science 2024-04-09 Shachar Rosenman , Vasudev Lal , Phillip Howard

Content creators often aim to create personalized images using personal subjects that go beyond the capabilities of conventional text-to-image models. Additionally, they may want the resulting image to encompass a specific location, style,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Moab Arar , Andrey Voynov , Amir Hertz , Omri Avrahami , Shlomi Fruchter , Yael Pritch , Daniel Cohen-Or , Ariel Shamir

Text-to-image models offer unprecedented freedom to guide creation through natural language. Yet, it is unclear how such freedom can be exercised to generate images of specific unique concepts, modify their appearance, or compose them in…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Rinon Gal , Yuval Alaluf , Yuval Atzmon , Or Patashnik , Amit H. Bermano , Gal Chechik , Daniel Cohen-Or

Recent text-to-image models excel at generating high-quality object-centric images from instructions. However, images should also encapsulate rich interactions between objects, where existing models often fall short, likely due to limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Xinyi Gu , Jiayuan Mao

We introduce Style Tailoring, a recipe to finetune Latent Diffusion Models (LDMs) in a distinct domain with high visual quality, prompt alignment and scene diversity. We choose sticker image generation as the target domain, as the images…

Large Language Models (LLMs), such as ChatGPT, exhibit advanced capabilities in generating text, images, and videos. However, their effective use remains constrained by challenges in prompt formulation, personalization, and opaque…

Human-Computer Interaction · Computer Science 2025-03-04 Si Thu , A. Baki Kocaballi

Text-to-image models give rise to workflows which often begin with an exploration step, where users sift through a large collection of generated images. The global nature of the text-to-image generation process prevents users from narrowing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Or Patashnik , Daniel Garibi , Idan Azuri , Hadar Averbuch-Elor , Daniel Cohen-Or

Well-designed prompts can guide text-to-image models to generate amazing images. However, the performant prompts are often model-specific and misaligned with user input. Instead of laborious human engineering, we propose prompt adaptation,…

Computation and Language · Computer Science 2024-01-01 Yaru Hao , Zewen Chi , Li Dong , Furu Wei

Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models often struggle with simple or underspecified prompts, leading to suboptimal image-text alignment, aesthetics, and quality. We propose a…

Computation and Language · Computer Science 2025-10-16 Ruibo Chen , Jiacheng Pan , Heng Huang , Zhenheng Yang

To address the challenge of information overload from massive web contents, recommender systems are widely applied to retrieve and present personalized results for users. However, recommendation tasks are inherently constrained to filtering…

Artificial Intelligence · Computer Science 2025-06-04 Jiongnan Liu , Zhicheng Dou , Ning Hu , Chenyan Xiong