English
Related papers

Related papers: PokeFusion Attention: A Lightweight Cross-Attentio…

200 papers

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

Recent text-to-image (T2I) diffusion models show outstanding performance in generating high-quality images conditioned on textual prompts. However, they fail to semantically align the generated images with the prompts due to their limited…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Ruichen Wang , Zekang Chen , Chen Chen , Jian Ma , Haonan Lu , Xiaodong Lin

Text-to-image (T2I) diffusion models, with their impressive generative capabilities, have been adopted for image editing tasks, demonstrating remarkable efficacy. However, due to attention leakage and collision between the cross-attention…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Xingxi Yin , Zhi Li , Jingfeng Zhang , Chenglin Li , Yin Zhang

Text-to-image (T2I) diffusion models have revolutionized generative modeling by producing high-fidelity, diverse, and visually realistic images from textual prompts. Despite these advances, existing models struggle with complex prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Eric Hanchen Jiang , Yasi Zhang , Zhi Zhang , Yixin Wan , Andrew Lizarraga , Shufan Li , Ying Nian Wu

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 (T2I) diffusion models lack an efficient mechanism for early quality assessment, leading to costly trial-and-error in multi-generation scenarios such as prompt iteration, agent-based generation, and flow-grpo. We reveal a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Benlei Cui , Bukun Huang , Zhizeng Ye , Xuemei Dong , Tuo Chen , Hui Xue , Dingkang Yang , Longtao Huang , Jingqun Tang , Haiwen Hong

The issue of generative pretraining for vision models has persisted as a long-standing conundrum. At present, the text-to-image (T2I) diffusion model demonstrates remarkable proficiency in generating high-definition images matching textual…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Qiang Wan , Zilong Huang , Bingyi Kang , Jiashi Feng , Li Zhang

Text-to-image synthesis has made significant progress, benefiting from the strong generative capabilities of diffusion models. However, these models struggle to achieve precise text-to-image alignment within cross-attention maps during the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Shipeng Cao , Biao Qian , Haipeng Liu , Yang Wang , Meng Wang

We present TokenCompose, a Latent Diffusion Model for text-to-image generation that achieves enhanced consistency between user-specified text prompts and model-generated images. Despite its tremendous success, the standard denoising process…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Zirui Wang , Zhizhou Sha , Zheng Ding , Yilin Wang , Zhuowen Tu

Recent advancements in diffusion models have notably improved the perceptual quality of generated images in text-to-image synthesis tasks. However, diffusion models often struggle to produce images that accurately reflect the intended…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Yang Zhang , Teoh Tze Tzun , Lim Wei Hern , Tiviatis Sim , Kenji Kawaguchi

Recent advancements in personalizing text-to-image (T2I) diffusion models have shown the capability to generate images based on personalized visual concepts using a limited number of user-provided examples. However, these models often…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Yan Hong , Jianfu Zhang

A significant research effort is focused on exploiting the amazing capacities of pretrained diffusion models for the editing of images.They either finetune the model, or invert the image in the latent space of the pretrained model. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Senmao Li , Joost van de Weijer , Taihang Hu , Fahad Shahbaz Khan , Qibin Hou , Yaxing Wang , Jian Yang , Ming-Ming Cheng

In layout-to-image (L2I) synthesis, controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

Diffusion-based models have achieved state-of-the-art performance on text-to-image synthesis tasks. However, one critical limitation of these models is the low fidelity of generated images with respect to the text description, such as…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Qiucheng Wu , Yujian Liu , Handong Zhao , Trung Bui , Zhe Lin , Yang Zhang , Shiyu Chang

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

Currently, personalized image generation methods mostly require considerable time to finetune and often overfit the concept resulting in generated images that are similar to custom concepts but difficult to edit by prompts. We propose an…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yuxuan Zhang , Yiren Song , Jinpeng Yu , Han Pan , Zhongliang Jing

Text-to-Image (T2I) generation methods based on diffusion model have garnered significant attention in the last few years. Although these image synthesis methods produce visually appealing results, they frequently exhibit spelling errors…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yiming Zhao , Zhouhui Lian

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 text-to-image generation tasks, the advancements of diffusion models have facilitated the fidelity of generated results. However, these models encounter challenges when processing text prompts containing multiple entities and attributes.…

Computation and Language · Computer Science 2024-04-23 Yihang Wu , Xiao Cao , Kaixin Li , Zitan Chen , Haonan Wang , Lei Meng , Zhiyong Huang

Optical illusion hidden picture is an interesting visual perceptual phenomenon where an image is cleverly integrated into another picture in a way that is not immediately obvious to the viewer. Established on the off-the-shelf text-to-image…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Xiang Gao , Shuai Yang , Jiaying Liu
‹ Prev 1 2 3 10 Next ›