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Recent breakthroughs in text-to-image diffusion models have significantly advanced the generation of high-fidelity, photo-realistic images from textual descriptions. Yet, these models often struggle with interpreting spatial arrangements…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Jiaqi Liu , Tao Huang , Chang Xu

Recently, many text-to-image diffusion models have excelled at generating high-resolution images from text but struggle with precise control over spatial composition and object counting. To address these challenges, prior works have…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Huancheng Chen , Jingtao Li , Weiming Zhuang , Haris Vikalo , Lingjuan Lyu

Text-to-image diffusion models exhibit remarkable generative capabilities, but lack precise control over object counts and spatial arrangements. This work introduces a two-stage system to address these compositional limitations. The first…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Jan-Hendrik Koch , Jonas Krumme , Konrad Gadzicki

Recent diffusion-based generators can produce high-quality images from textual prompts. However, they often disregard textual instructions that specify the spatial layout of the composition. We propose a simple approach that achieves robust…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Minghao Chen , Iro Laina , Andrea Vedaldi

Based on recent advanced diffusion models, Text-to-image (T2I) generation models have demonstrated their capabilities to generate diverse and high-quality images. However, leveraging their potential for real-world content creation,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Sandra Zhang Ding , Jiafeng Mao , Kiyoharu Aizawa

Recent text-to-image diffusion models have reached an unprecedented level in generating high-quality images. However, their exclusive reliance on textual prompts often falls short in precise control of image compositions. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Peiang Zhao , Han Li , Ruiyang Jin , S. Kevin Zhou

Recently, diffusion models have achieved great success in image synthesis. However, when it comes to the layout-to-image generation where an image often has a complex scene of multiple objects, how to make strong control over both the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Guangcong Zheng , Xianpan Zhou , Xuewei Li , Zhongang Qi , Ying Shan , Xi Li

The task of layout-to-image generation involves synthesizing images based on the captions of objects and their spatial positions. Existing methods still struggle in complex layout generation, where common bad cases include object missing,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Bo Cheng , Yuhang Ma , Liebucha Wu , Shanyuan Liu , Ao Ma , Xiaoyu Wu , Dawei Leng , Yuhui Yin

Layout-to-Image generation aims to create complex scenes with precise control over the placement and arrangement of subjects. Existing works have demonstrated that pre-trained Text-to-Image diffusion models can achieve this goal without…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Bonan Li , Yinhan Hu , Songhua Liu , Xinchao Wang

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

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

Driven by the scalable diffusion models trained on large-scale datasets, text-to-image synthesis methods have shown compelling results. However, these models still fail to precisely follow the text prompt involving multiple objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Quynh Phung , Songwei Ge , Jia-Bin Huang

Diffusion models are a powerful class of generative models capable of producing high-quality images from pure noise using a simple text prompt. While most methods which introduce additional spatial constraints into the generated images…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Zakaria Patel , Kirill Serkh

As powerful generative models, text-to-image diffusion models have recently been explored for discriminative tasks. A line of research focuses on adapting a pre-trained diffusion model to semantic segmentation without any further training,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Benyuan Meng , Qianqian Xu , Zitai Wang , Xiaochun Cao , Longtao Huang , Qingming Huang

Recent advancements in generative models have significantly enhanced their capacity for image generation, enabling a wide range of applications such as image editing, completion and video editing. A specialized area within generative…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Jiaxin Cheng , Zixu Zhao , Tong He , Tianjun Xiao , Yicong Zhou , Zheng Zhang

Controllable text-to-image generation synthesizes visual text and objects in images with certain conditions, which are frequently applied to emoji and poster generation. Visual text rendering and layout-to-image generation tasks have been…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Xiaoran Zhao , Tianhao Wu , Yu Lai , Zhiliang Tian , Zhen Huang , Yahui Liu , Zejiang He , Dongsheng Li

Diffusion models have exhibit exceptional performance in text-to-image generation and editing. However, existing methods often face challenges when handling complex text prompts that involve multiple objects with multiple attributes and…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ling Yang , Zhaochen Yu , Chenlin Meng , Minkai Xu , Stefano Ermon , Bin Cui

While text-to-image diffusion models can generate highquality images from textual descriptions, they generally lack fine-grained control over the visual composition of the generated images. Some recent works tackle this problem by training…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Denis Lukovnikov , Asja Fischer

Recent text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images given text-prompts as input. However, these models fail to convey appropriate spatial composition specified by a layout…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Jiayu Xiao , Henglei Lv , Liang Li , Shuhui Wang , Qingming Huang

Attention mechanism has been crucial for image diffusion models, however, their quadratic computational complexity limits the sizes of images we can process within reasonable time and memory constraints. This paper investigates the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Ethan Smith , Nayan Saxena , Aninda Saha
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