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Text-to-image generative models have recently exploded in popularity and accessibility. Yet so far, use of these models in creative tasks that bridge the 2D digital world and the creation of physical artefacts has been understudied. We…

Artificial Intelligence · Computer Science 2023-02-02 Amy Smith , Hope Schroeder , Ziv Epstein , Michael Cook , Simon Colton , Andrew Lippman

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

Text-to-image (T2I) generation has made significant advances in recent years, but challenges still remain in the generation of perceptual artifacts, misalignment with complex prompts, and safety. The prevailing approach to address these…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Xiaoying Xing , Avinab Saha , Junfeng He , Susan Hao , Paul Vicol , Moonkyung Ryu , Gang Li , Sahil Singla , Sarah Young , Yinxiao Li , Feng Yang , Deepak Ramachandran

Sketching is a widely used medium for generating and exploring early-stage design concepts. While generative AI (GenAI) chatbots are increasingly used for idea generation, designers often struggle to craft effective prompts and find it…

Human-Computer Interaction · Computer Science 2025-11-19 Weiyan Shi , Sunaya Upadhyay , Geraldine Quek , Kenny Tsu Wei Choo

Procedural textures are normally generated from mathematical models with parameters carefully selected by experienced users. However, for naive users, the intuitive way to obtain a desired texture is to provide semantic descriptions such as…

Computer Vision and Pattern Recognition · Computer Science 2017-04-14 Junyu Dong , Lina Wang , Jun Liu , Xin Sun

Recent advancements in large vision-language models have enabled highly expressive and diverse vector sketch generation. However, state-of-the-art methods rely on a time-consuming optimization process involving repeated feedback from a…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Ellie Arar , Yarden Frenkel , Daniel Cohen-Or , Ariel Shamir , Yael Vinker

We present a novel task: text-to-3D sketch animation, which aims to bring freeform sketches to life in dynamic 3D space. Unlike prior works focused on photorealistic content generation, we target sparse, stylized, and view-consistent 3D…

Graphics · Computer Science 2025-10-30 Hao Chen , Jiaqi Wang , Yonggang Qi , Ke Li , Kaiyue Pang , Yi-Zhe Song

Recent advancements in text-to-image diffusion models have demonstrated remarkable success, yet they often struggle to fully capture the user's intent. Existing approaches using textual inputs combined with bounding boxes or region masks…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Seonho Lee , Jiho Choi , Seohyun Lim , Jiwook Kim , Hyunjung Shim

The significant progress on Generative Adversarial Networks (GANs) have made it possible to generate surprisingly realistic images for single object based on natural language descriptions. However, controlled generation of images for…

Computer Vision and Pattern Recognition · Computer Science 2019-11-14 Hongdong Zheng , Yalong Bai , Wei Zhang , Tao Mei

Generating sketches guided by reference styles requires precise transfer of stroke attributes, such as line thickness, deformation, and texture sparsity, while preserving semantic structure and content fidelity. To this end, we propose…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Rui Yang , Huining Li , Yiyi Long , Xiaojun Wu , Shengfeng He

Diffusion models have exhibited substantial success in text-to-image generation. However, they often encounter challenges when dealing with complex and dense prompts involving multiple objects, attribute binding, and long descriptions. In…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Mushui Liu , Yuhang Ma , Yang Zhen , Jun Dan , Yunlong Yu , Zeng Zhao , Zhipeng Hu , Bai Liu , Changjie Fan

Controllable image semantic understanding tasks, such as captioning or segmentation, necessitate users to input a prompt (e.g., text or bounding boxes) to predict a unique outcome, presenting challenges such as high-cost prompt input or…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Xu Zhang , Jin Yuan , Hanwang Zhang , Guojin Zhong , Yongsheng Zang , Jiacheng Lin , Zhiyong Li

Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating multilingual scene text images. To tackle this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Lingjun Zhang , Xinyuan Chen , Yaohui Wang , Yue Lu , Yu Qiao

Generating images from hand-drawings is a crucial and fundamental task in content creation. The translation is difficult as there exist infinite possibilities and the different users usually expect different outcomes. Therefore, we propose…

Computer Vision and Pattern Recognition · Computer Science 2022-09-02 Shin-I Cheng , Yu-Jie Chen , Wei-Chen Chiu , Hung-Yu Tseng , Hsin-Ying Lee

We propose a novel hierarchical approach for text-to-image synthesis by inferring semantic layout. Instead of learning a direct mapping from text to image, our algorithm decomposes the generation process into multiple steps, in which it…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Seunghoon Hong , Dingdong Yang , Jongwook Choi , Honglak Lee

Recent advances in text-to-image generation have improved the quality of synthesized images, but evaluations mainly focus on aesthetics or alignment with text prompts. Thus, it remains unclear whether these models can accurately represent a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Hsin-Ping Huang , Xinyi Wang , Yonatan Bitton , Hagai Taitelbaum , Gaurav Singh Tomar , Ming-Wei Chang , Xuhui Jia , Kelvin C. K. Chan , Hexiang Hu , Yu-Chuan Su , Ming-Hsuan Yang

The field of controllable image generation has seen significant advancements, with various architectures improving generation layout consistency with control signals. However, contemporary methods still face challenges in bridging the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Feng Han , Yang Jiao , Shaoxiang Chen , Junhao Xu , Jingjing Chen , Yu-Gang Jiang

Sketching is a powerful artistic technique for capturing essential visual information about real-world objects and has increasingly attracted attention in image synthesis research. However, the field lacks a unified benchmark to evaluate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Xingyue Lin , Xingjian Hu , Shuai Peng , Jianhua Zhu , Liangcai Gao

Despite significant progress in the field, it is still challenging to create personalized visual representations that align closely with the desires and preferences of individual users. This process requires users to articulate their ideas…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Zijie Chen , Lichao Zhang , Fangsheng Weng , Lili Pan , Zhenzhong Lan

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua