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Text-to-image synthesis refers to generating visual-realistic and semantically consistent images from given textual descriptions. Previous approaches generate an initial low-resolution image and then refine it to be high-resolution. Despite…

Computer Vision and Pattern Recognition · Computer Science 2023-02-21 Haoran Sun , Yang Wang , Haipeng Liu , Biao Qian

Text-to-image (T2I) models, such as Stable Diffusion, have exhibited remarkable performance in generating high-quality images from text descriptions in recent years. However, text-to-image models may be tricked into generating…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Xinfeng Li , Yuchen Yang , Jiangyi Deng , Chen Yan , Yanjiao Chen , Xiaoyu Ji , Wenyuan Xu

Modern text-to-image synthesis models have achieved an exceptional level of photorealism, generating high-quality images from arbitrary text descriptions. In light of the impressive synthesis ability, several studies have exhibited…

Computer Vision and Pattern Recognition · Computer Science 2023-06-13 Joonghyuk Shin , Minguk Kang , Jaesik Park

Image-to-image (I2I) translation methods based on generative adversarial networks (GANs) typically suffer from overfitting when limited training data is available. In this work, we propose a data augmentation method (ReMix) to tackle this…

Computer Vision and Pattern Recognition · Computer Science 2021-04-01 Jie Cao , Luanxuan Hou , Ming-Hsuan Yang , Ran He , Zhenan Sun

Prevailing autoregressive (AR) models for text-to-image generation either rely on heavy, computationally-intensive diffusion models to process continuous image tokens, or employ vector quantization (VQ) to obtain discrete tokens with…

Common image-text joint understanding techniques presume that images and the associated text can universally be characterized by a single implicit model. However, co-occurring images and text can be related in qualitatively different ways,…

Computer Vision and Pattern Recognition · Computer Science 2022-04-18 Malihe Alikhani , Fangda Han , Hareesh Ravi , Mubbasir Kapadia , Vladimir Pavlovic , Matthew Stone

Recent text-to-image models have achieved impressive results. However, since they require large-scale datasets of text-image pairs, it is impractical to train them on new domains where data is scarce or not labeled. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Shelly Sheynin , Oron Ashual , Adam Polyak , Uriel Singer , Oran Gafni , Eliya Nachmani , Yaniv Taigman

We introduce ``Idea to Image,'' a system that enables multimodal iterative self-refinement with GPT-4V(ision) for automatic image design and generation. Humans can quickly identify the characteristics of different text-to-image (T2I) models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Zhengyuan Yang , Jianfeng Wang , Linjie Li , Kevin Lin , Chung-Ching Lin , Zicheng Liu , Lijuan Wang

Fine-grained text to image synthesis involves generating images from texts that belong to different categories. In contrast to general text to image synthesis, in fine-grained synthesis there is high similarity between images of different…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Xu Ouyang , Ying Chen , Kaiyue Zhu , Gady Agam

Exams are a fundamental test of expert-level intelligence and require integrated understanding, reasoning, and generation. Existing exam-style benchmarks mainly focus on understanding and reasoning tasks, and current generation benchmarks…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Zhaokai Wang , Penghao Yin , Xiangyu Zhao , Changyao Tian , Yu Qiao , Wenhai Wang , Jifeng Dai , Gen Luo

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

In the e-commerce realm, compelling advertising images are pivotal for attracting customer attention. While generative models automate image generation, they often produce substandard images that may mislead customers and require…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Zhenbang Du , Wei Feng , Haohan Wang , Yaoyu Li , Jingsen Wang , Jian Li , Zheng Zhang , Jingjing Lv , Xin Zhu , Junsheng Jin , Junjie Shen , Zhangang Lin , Jingping Shao

Text-to-image generation models have grown in popularity due to their ability to produce high-quality images from a text prompt. One use for this technology is to enable the creation of more accessible art creation software. In this paper,…

Human-Computer Interaction · Computer Science 2023-09-06 Atieh Taheri , Mohammad Izadi , Gururaj Shriram , Negar Rostamzadeh , Shaun Kane

Recent studies have shown remarkable success in the unsupervised image to image (I2I) translation. However, due to the imbalance in the data, learning joint distribution for various domains is still very challenging. Although existing…

Computer Vision and Pattern Recognition · Computer Science 2021-06-24 Jihye Back

Recent advances in personalized image generation allow a pre-trained text-to-image model to learn a new concept from a set of images. However, existing personalization approaches usually require heavy test-time finetuning for each concept,…

Computer Vision and Pattern Recognition · Computer Science 2023-04-10 Jing Shi , Wei Xiong , Zhe Lin , Hyun Joon Jung

Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text. However, these pre-trained models often face challenges when it comes to generating highly aesthetic images.…

Text-to-Image translation has been an active area of research in the recent past. The ability for a network to learn the meaning of a sentence and generate an accurate image that depicts the sentence shows ability of the model to think more…

Machine Learning · Computer Science 2018-08-15 Satya Krishna Gorti , Jeremy Ma

The increasing demand for online fashion retail has boosted research in fashion compatibility modeling and item retrieval, focusing on matching user queries (textual descriptions or reference images) with compatible fashion items. A key…

Information Retrieval · Computer Science 2026-05-19 Matteo Attimonelli , Claudio Pomo , Dietmar Jannach , Tommaso Di Noia

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

Text-to-image diffusion models have demonstrated remarkable capability in generating realistic images from arbitrary text prompts. However, they often produce inconsistent results for compositional prompts such as "two dogs" or "a penguin…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Shuangqi Li , Hieu Le , Jingyi Xu , Mathieu Salzmann