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Text-to-image (T2I) generative diffusion models have demonstrated outstanding performance in synthesizing diverse, high-quality visuals from text captions. Several layout-to-image models have been developed to control the generation process…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Ahmad Süleyman , Göksel Biricik

Text-to-Image (T2I) diffusion models have shown impressive results in generating visually compelling images following user prompts. Building on this, various methods further fine-tune the pre-trained T2I model for specific tasks. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-24 Tsu-Jui Fu , Yusu Qian , Chen Chen , Wenze Hu , Zhe Gan , Yinfei Yang

Multimedia generation approaches occupy a prominent place in artificial intelligence research. Text-to-image models achieved high-quality results over the last few years. However, video synthesis methods recently started to develop. This…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Vladimir Arkhipkin , Zein Shaheen , Viacheslav Vasilev , Elizaveta Dakhova , Andrey Kuznetsov , Denis Dimitrov

The revolution of artificial intelligence content generation has been rapidly accelerated with the booming text-to-image (T2I) diffusion models. Within just two years of development, it was unprecedentedly of high-quality, diversity, and…

Artificial Intelligence · Computer Science 2023-10-16 Zeqiang Lai , Xizhou Zhu , Jifeng Dai , Yu Qiao , Wenhai Wang

Large-scale diffusion models have achieved state-of-the-art results on text-to-image synthesis (T2I) tasks. Despite their ability to generate high-quality yet creative images, we observe that attribution-binding and compositional…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Weixi Feng , Xuehai He , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , Xin Eric Wang , William Yang Wang

Large-scale text-to-image diffusion models have been a revolutionary milestone in the evolution of generative AI and multimodal technology, allowing wonderful image generation with natural-language text prompt. However, the issue of lacking…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Xiang Gao , Jiaying Liu

Large diffusion-based Text-to-Image (T2I) models have shown impressive generative powers for text-to-image generation as well as spatially conditioned image generation. For most applications, we can train the model end-toend with paired…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Nithin Gopalakrishnan Nair , Jeya Maria Jose Valanarasu , Vishal M Patel

In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guided generative functions. However, relying solely on text for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Pu Cao , Feng Zhou , Qing Song , Lu Yang

Large-scale, pre-trained Text-to-Image (T2I) diffusion models have gained significant popularity in image generation tasks and have shown unexpected potential in image Super-Resolution (SR). However, most existing T2I diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Brian B. Moser , Stanislav Frolov , Tobias C. Nauen , Federico Raue , Andreas Dengel

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

Video generation has increasingly gained interest in both academia and industry. Although commercial tools can generate plausible videos, there is a limited number of open-source models available for researchers and engineers. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Haoxin Chen , Menghan Xia , Yingqing He , Yong Zhang , Xiaodong Cun , Shaoshu Yang , Jinbo Xing , Yaofang Liu , Qifeng Chen , Xintao Wang , Chao Weng , Ying Shan

Text-to-image (T2I) customization aims to create images that embody specific visual concepts delineated in textual descriptions. However, existing works still face a main challenge, concept overfitting. To tackle this challenge, we first…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Weili Zeng , Yichao Yan , Qi Zhu , Zhuo Chen , Pengzhi Chu , Weiming Zhao , Xiaokang Yang

With the help of conditioning mechanisms, the state-of-the-art diffusion models have achieved tremendous success in guided image generation, particularly in text-to-image synthesis. To gain a better understanding of the training process and…

Cryptography and Security · Computer Science 2023-10-24 Shengfang Zhai , Yinpeng Dong , Qingni Shen , Shi Pu , Yuejian Fang , Hang Su

Generative modeling is widely regarded as one of the most essential problems in today's AI community, with text-to-image generation having gained unprecedented real-world impacts. Among various approaches, diffusion models have achieved…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xuyang Guo , Jiayan Huo , Yingyu Liang , Zhenmei Shi , Zhao Song , Jiahao Zhang , Zhen Zhuang

Over the past few years, Text-to-Image (T2I) generation approaches based on diffusion models have gained significant attention. However, vanilla diffusion models often suffer from spelling inaccuracies in the text displayed within the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Sanyam Lakhanpal , Shivang Chopra , Vinija Jain , Aman Chadha , Man Luo

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

With the rapid development of diffusion models, text-to-image(T2I) models have made significant progress, showcasing impressive abilities in prompt following and image generation. Recently launched models such as FLUX.1 and Ideogram2.0,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Jiayi Lei , Renrui Zhang , Xiangfei Hu , Weifeng Lin , Zhen Li , Wenjian Sun , Ruoyi Du , Le Zhuo , Zhongyu Li , Xinyue Li , Shitian Zhao , Ziyu Guo , Yiting Lu , Peng Gao , Hongsheng Li

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

With large-scale text-to-image (T2I) diffusion models achieving significant advancements in open-domain image creation, increasing attention has been focused on their natural extension to the realm of text-driven image-to-image (I2I)…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Xiang Gao , Yunpeng Jia

Most text-to-3D generators build upon off-the-shelf text-to-image models trained on billions of images. They use variants of Score Distillation Sampling (SDS), which is slow, somewhat unstable, and prone to artifacts. A mitigation is to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Luke Melas-Kyriazi , Iro Laina , Christian Rupprecht , Natalia Neverova , Andrea Vedaldi , Oran Gafni , Filippos Kokkinos