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Image inpainting is the task of reconstructing missing or damaged parts of an image in a way that seamlessly blends with the surrounding content. With the advent of advanced generative models, especially diffusion models and generative…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Xingzhong Hou , Jie Wu , Boxiao Liu , Yi Zhang , Guanglu Song , Yunpeng Liu , Yu Liu , Haihang You

Text-to-image models have made significant strides, producing impressive results in generating images from textual descriptions. However, creating a scalable pipeline for deploying these models in production remains a challenge. Achieving…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Parmida Atighehchian , Henry Wang , Andrei Kapustin , Boris Lerner , Tiancheng Jiang , Taylor Jensen , Negin Sokhandan

While text-to-image (T2I) models can synthesize high-quality images, their performance degrades significantly when prompted with novel or out-of-distribution (OOD) entities due to inherent knowledge cutoffs. We introduce World-To-Image, a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Moo Hyun Son , Jintaek Oh , Sun Bin Mun , Jaechul Roh , Sehyun Choi

Prompt-driven image analysis converts a single natural-language instruction into multiple steps: locate, segment, edit, and describe. We present a practical case study of a unified pipeline that combines open-vocabulary detection,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 Kaleem Ahmad

Despite rapid advancements in the capabilities of generative models, pretrained text-to-image models still struggle in capturing the semantics conveyed by complex prompts that compound multiple objects and instance-level attributes.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Etai Sella , Yanir Kleiman , Hadar Averbuch-Elor

Multilingual text-to-image (T2I) models have advanced rapidly in terms of visual realism and semantic alignment, and are now widely utilized. Yet outputs vary across cultural contexts: because language carries cultural connotations, images…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Chuancheng Shi , Shangze Li , Shiming Guo , Simiao Xie , Wenhua Wu , Jingtong Dou , Chao Wu , Canran Xiao , Cong Wang , Zifeng Cheng , Fei Shen , Tat-Seng Chua

Text-to-Image (TTI) generative models have shown great progress in the past few years in terms of their ability to generate complex and high-quality imagery. At the same time, these models have been shown to suffer from harmful biases,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Aditya Chinchure , Pushkar Shukla , Gaurav Bhatt , Kiri Salij , Kartik Hosanagar , Leonid Sigal , Matthew Turk

Text-to-image generative models have increasingly been used to assist designers during concept generation in various creative domains, such as graphic design, user interface design, and fashion design. However, their applications in…

Artificial Intelligence · Computer Science 2024-07-23 Leah Chong , Jude Rayan , Steven Dow , Ioanna Lykourentzou , Faez Ahmed

The stories and characters that captivate us as we grow up shape unique fantasy worlds, with images serving as the primary medium for visually experiencing these realms. Personalizing generative models through fine-tuning with…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Yuxin Zhang , Minyan Luo , Weiming Dong , Xiao Yang , Haibin Huang , Chongyang Ma , Oliver Deussen , Tong-Yee Lee , Changsheng Xu

Beyond conveying semantic information, images also possess cognitive properties that elicit specific psychological responses from viewers, such as memory encoding or emotional reactions. Although modern text-to-image (T2I) models generate…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Shengqi Dang , Yi He , Jiaying Lei , Ziqing Qian , Nan Cao

Image editing has advanced significantly with the introduction of text-conditioned diffusion models. Despite this progress, seamlessly adding objects to images based on textual instructions without requiring user-provided input masks…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Navve Wasserman , Noam Rotstein , Roy Ganz , Ron Kimmel

Recent text-to-image (T2I) models have made remarkable progress in generating visually realistic and semantically coherent images. However, they still suffer from randomness and inconsistency with the given prompts, particularly when…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Kaishen Wang , Ruibo Chen , Tong Zheng , Heng Huang

Authoring realistic haptic textures typically requires low-level parameter tuning and repeated trial-and-error, limiting speed, transparency, and creative reach. We present a language-driven authoring system that turns natural-language…

Human-Computer Interaction · Computer Science 2026-04-09 Wanli Qian , Aiden Chang , Shihan Lu , Michael Gu , Heather Culbertson

The progress in the generation of synthetic images has made it crucial to assess their quality. While several metrics have been proposed to assess the rendering of images, it is crucial for Text-to-Image (T2I) models, which generate images…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Paul Grimal , Hervé Le Borgne , Olivier Ferret , Julien Tourille

We introduce PromptCanvas, a concept that transforms prompting into a composable, widget-based experience on an infinite canvas. Users can generate, customize, and arrange interactive widgets representing various facets of their text,…

Human-Computer Interaction · Computer Science 2025-06-05 Rifat Mehreen Amin , Oliver Hans Kühle , Daniel Buschek , Andreas Butz

This paper presents a real-time generative drawing system that interprets and integrates both formal intent - the structural, compositional, and stylistic attributes of a sketch - and contextual intent - the semantic and thematic meaning…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Jookyung Song , Mookyoung Kang , Nojun Kwak

Creative generation is the synthesis of new, surprising, and valuable samples that reflect user intent yet cannot be envisioned in advance. This task aims to extend human imagination, enabling the discovery of visual concepts that exist in…

Graphics · Computer Science 2025-10-14 Shelly Golan , Yotam Nitzan , Zongze Wu , Or Patashnik

Large-scale Text-to-Image (T2I) models have rapidly gained prominence across creative fields, generating visually compelling outputs from textual prompts. However, controlling these models to ensure consistent style remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Amir Hertz , Andrey Voynov , Shlomi Fruchter , Daniel Cohen-Or

Text-to-image generative models can produce diverse high-quality images of concepts with a text prompt, which have demonstrated excellent ability in image generation, image translation, etc. We in this work study the problem of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-09-11 Gan Sun , Wenqi Liang , Jiahua Dong , Jun Li , Zhengming Ding , Yang Cong

Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially utilize image inputs, focusing on specific elements like…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Teng-Fang Hsiao , Bo-Kai Ruan , Yi-Lun Wu , Tzu-Ling Lin , Hong-Han Shuai
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