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Text-to-Image (T2I) diffusion models have achieved remarkable success in image generation. Despite their progress, challenges remain in both prompt-following ability, image quality and lack of high-quality datasets, which are essential for…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Jingkun An , Yinghao Zhu , Zongjian Li , Enshen Zhou , Haoran Feng , Xijie Huang , Bohua Chen , Yemin Shi , Chengwei Pan

We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large transformer language models in understanding text and hinges on…

Previous text-to-image synthesis algorithms typically use explicit textual instructions to generate/manipulate images accurately, but they have difficulty adapting to guidance in the form of coarsely matched texts. In this work, we attempt…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Mengyao Cui , Zhe Zhu , Shao-Ping Lu , Yulu Yang

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

Text-to-Image and Text-to-Video AI generation models are revolutionary technologies that use deep learning and natural language processing (NLP) techniques to create images and videos from textual descriptions. This paper investigates…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Aditi Singh

Large Text-to-Image(T2I) diffusion models have shown a remarkable capability to produce photorealistic and diverse images based on text inputs. However, existing works only support limited language input, e.g., English, Chinese, and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-24 Fulong Ye , Guang Liu , Xinya Wu , Ledell Wu

Text-to-video generation has trailed behind text-to-image generation in terms of quality and diversity, primarily due to the inherent complexities of spatio-temporal modeling and the limited availability of video-text datasets. Recent…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Xiefan Guo , Jinlin Liu , Miaomiao Cui , Liefeng Bo , Di Huang

This work aims to create a multimodal AI system that chats with humans and shares relevant photos. While earlier works were limited to dialogues about specific objects or scenes within images, recent works have incorporated images into…

Computation and Language · Computer Science 2023-05-08 Min Young Lee

The emergence of diffusion models has significantly advanced image synthesis. The recent studies of model interaction and self-corrective reasoning approach in large language models offer new insights for enhancing text-to-image models.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Zhongjie Duan , Qianyi Zhao , Cen Chen , Daoyuan Chen , Wenmeng Zhou , Yaliang Li , Yingda Chen

Despite their wide-spread success, Text-to-Image models (T2I) still struggle to produce images that are both aesthetically pleasing and faithful to the user's input text. We introduce DreamSync, a model-agnostic training algorithm by design…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Jiao Sun , Deqing Fu , Yushi Hu , Su Wang , Royi Rassin , Da-Cheng Juan , Dana Alon , Charles Herrmann , Sjoerd van Steenkiste , Ranjay Krishna , Cyrus Rashtchian

Layout-guided text-to-image models offer greater control over the generation process by explicitly conditioning image synthesis on the spatial arrangement of elements. As a result, their adoption has increased in many computer vision…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Elena Izzo , Luca Parolari , Davide Vezzaro , Lamberto Ballan

Automating Text-to-Image (T2I) model evaluation is challenging; a judge model must be used to score correctness, and test prompts must be selected to be challenging for current T2I models but not the judge. We argue that satisfying these…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Amita Kamath , Kai-Wei Chang , Ranjay Krishna , Luke Zettlemoyer , Yushi Hu , Marjan Ghazvininejad

Large-scale text-to-image diffusion models have been a ground-breaking development in generating convincing images following an input text prompt. The goal of image editing research is to give users control over the generated images by…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Chuanming Tang , Kai Wang , Joost van de Weijer

A significant ``modality gap" exists between the abundance of text-only data and the increasing power of multimodal models. This work systematically investigates whether images generated on-the-fly by Text-to-Image (T2I) models can serve as…

Multimedia · Computer Science 2026-03-04 Yuesheng Huang , Peng Zhang , Xiaoxin Wu , Riliang Liu , Jiaqi Liang

We present Infinite-Story, a training-free framework for consistent text-to-image (T2I) generation tailored for multi-prompt storytelling scenarios. Built upon a scale-wise autoregressive model, our method addresses two key challenges in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Jihun Park , Kyoungmin Lee , Jongmin Gim , Hyeonseo Jo , Minseok Oh , Wonhyeok Choi , Kyumin Hwang , Jaeyeul Kim , Minwoo Choi , Sunghoon Im

Artificial Intelligence-Generated Content (AIGC) has made significant strides, with high-resolution text-to-image (T2I) generation becoming increasingly critical for improving users' Quality of Experience (QoE). Although…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Chongbin Yi , Yuxin Liang , Ziqi Zhou , Peng Yang

Powerful generative adversarial networks (GAN) have been developed to automatically synthesize realistic images from text. However, most existing tasks are limited to generating simple images such as flowers from captions. In this work, we…

Machine Learning · Computer Science 2019-11-27 Osaid Rehman Nasir , Shailesh Kumar Jha , Manraj Singh Grover , Yi Yu , Ajit Kumar , Rajiv Ratn Shah

Recent years have witnessed remarkable progress in image generation task, where users can create visually astonishing images with high-quality. However, existing text-to-image diffusion models are proficient in generating concrete concepts…

Computer Vision and Pattern Recognition · Computer Science 2024-01-10 Jingyuan Yang , Jiawei Feng , Hui Huang

Recent advances in text-to-video (T2V) technology, as demonstrated by models such as Runway Gen-3, Pika, Sora, and Kling, have significantly broadened the applicability and popularity of the technology. This progress has created a growing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Zelu Qi , Ping Shi , Shuqi Wang , Chaoyang Zhang , Fei Zhao , Zefeng Ying , Da Pan , Xi Yang , Zheqi He , Teng Dai

Humans often specify and create through visual artifacts: typography sheets, sketches, reference images, and annotated scenes. Yet modern visual generators still ask users to serialize this intent into text, a bottleneck that compresses…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Yaofang Liu , Kangning Cui , Meng Chu , Zhaoqing Li , Suiyun Zhang , Jean-Michel Morel , Xiaodong Cun , Haoxuan Che , Rui Liu , Raymond H. Chan