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Related papers: SYNTHIA: Novel Concept Design with Affordance Comp…

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Reasoning the human-object interactions (HOI) is essential for deeper scene understanding, while object affordances (or functionalities) are of great importance for human to discover unseen HOIs with novel objects. Inspired by this, we…

Computer Vision and Pattern Recognition · Computer Science 2022-03-30 Zhi Hou , Baosheng Yu , Yu Qiao , Xiaojiang Peng , Dacheng Tao

In this paper, we present DesignDiffusion, a simple yet effective framework for the novel task of synthesizing design images from textual descriptions. A primary challenge lies in generating accurate and style-consistent textual and visual…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Zhendong Wang , Jianmin Bao , Shuyang Gu , Dong Chen , Wengang Zhou , Houqiang Li

Recent advances in text-to-image synthesis largely benefit from sophisticated sampling strategies and classifier-free guidance (CFG) to ensure high-quality generation. However, CFG's reliance on two forward passes, especially when combined…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Minghao Fu , Guo-Hua Wang , Xiaohao Chen , Qing-Guo Chen , Zhao Xu , Weihua Luo , Kaifu Zhang

The scarcity of annotated surgical data poses a significant challenge for developing deep learning systems in computer-assisted interventions. While diffusion models can synthesize realistic images, they often suffer from data memorization,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Danush Kumar Venkatesh , Stefanie Speidel

Despite advances in generation quality, current text-to-image (T2I) models often lack diversity, generating homogeneous outputs. This work introduces a framework to address the need for robust diversity evaluation in T2I models. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Isabela Albuquerque , Ira Ktena , Olivia Wiles , Ivana Kajić , Amal Rannen-Triki , Cristina Vasconcelos , Aida Nematzadeh

Current text-to-image (T2I) generation models struggle to align spatial composition with the input text, especially in complex scenes. Even layout-based approaches yield suboptimal spatial control, as their generation process is decoupled…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Zheyuan Liu , Munan Ning , Qihui Zhang , Shuo Yang , Zhongrui Wang , Yiwei Yang , Xianzhe Xu , Yibing Song , Weihua Chen , Fan Wang , Li Yuan

Removing unwanted concepts from large-scale text-to-image (T2I) diffusion models while maintaining their overall generative quality remains an open challenge. This difficulty is especially pronounced in emerging paradigms, such as Stable…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Daiheng Gao , Shilin Lu , Shaw Walters , Wenbo Zhou , Jiaming Chu , Jie Zhang , Bang Zhang , Mengxi Jia , Jian Zhao , Zhaoxin Fan , Weiming Zhang

Integrating multiple personalized concepts into a single image has recently gained attention in text-to-image (T2I) generation. However, existing methods often suffer from performance degradation in complex scenes due to distortions in…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Young Beom Woo , Sun Eung Kim , Seong-Whan Lee

Blending visual and textual concepts into a new visual concept is a unique and powerful trait of human beings that can fuel creativity. However, in practice, cross-modal conceptual blending for humans is prone to cognitive biases, like…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Wonwoong Cho , Yanxia Zhang , Yan-Ying Chen , David I. Inouye

We introduce a general framework for generating diverse visual content, including ambiguous images, panorama images, mesh textures, and Gaussian splat textures, by synchronizing multiple diffusion processes. We present exhaustive…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Jaihoon Kim , Juil Koo , Kyeongmin Yeo , Minhyuk Sung

Text-to-image (T2I) customization empowers users to adapt the T2I diffusion model to new concepts absent in the pre-training dataset. On this basis, capturing multiple new concepts from a single image has emerged as a new task, allowing the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Junjie Shentu , Matthew Watson , Noura Al Moubayed

We present a novel and effective approach for generating new clothing on a wearer through generative adversarial learning. Given an input image of a person and a sentence describing a different outfit, our model "redresses" the person as…

Computer Vision and Pattern Recognition · Computer Science 2017-10-23 Shizhan Zhu , Sanja Fidler , Raquel Urtasun , Dahua Lin , Chen Change Loy

A well-designed document communicates not only through its words but also through its visual eloquence. Authors utilize aesthetic elements such as colors, fonts, graphics, and layouts to shape the perception of information. Thoughtful…

Artificial Intelligence · Computer Science 2024-03-28 Hsiu-Wei Yang , Abhinav Agrawal , Pavlos Fragkogiannis , Shubham Nitin Mulay

Creating thematic collections in industries demands innovative designs and cohesive concepts. Designers may face challenges in maintaining thematic consistency when drawing inspiration from existing objects, landscapes, or artifacts. While…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Dinh-Khoi Vo , Duy-Nam Ly , Khanh-Duy Le , Tam V. Nguyen , Minh-Triet Tran , Trung-Nghia Le

State-of-the-art text-to-image (T2I) diffusion models often struggle to generate rare compositions of concepts, e.g., objects with unusual attributes. In this paper, we show that the compositional generation power of diffusion models on…

Machine Learning · Computer Science 2025-09-30 Dongmin Park , Sebin Kim , Taehong Moon , Minkyu Kim , Kangwook Lee , Jaewoong Cho

Text-to-Image In-Context Learning (T2I-ICL) enables customized image synthesis via interleaved text-image examples but faces two mutually reinforcing bottlenecks, compliance failure and prior-dominated hallucination, that form a vicious…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Zhiyong Ma , Zhenpeng Li , Yuanjie Shi , Zhengping Li , Jiahao Chen , Qingyuan Chuai

Compositionality is believed to be fundamental to intelligence. In humans, it underlies the structure of thought, language, and higher-level reasoning. In AI, compositional representations can enable a powerful form of out-of-distribution…

Computation and Language · Computer Science 2025-06-04 Eric Elmoznino , Thomas Jiralerspong , Yoshua Bengio , Guillaume Lajoie

Composition is a cornerstone of visual aesthetics, influencing the appeal of an image. While its principles operate independently of specific content, in practice, composition is often coupled with semantics. As a result, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Kai Zou , Zhiwei Zhao , Bin Liu , Nenghai Yu

Recent thrilling progress in large-scale text-to-image (T2I) models has unlocked unprecedented synthesis quality of AI-generated content (AIGC) including image generation, 3D and video composition. Further, personalized techniques enable…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Yanbing Zhang , Mengping Yang , Qin Zhou , Zhe Wang

Generative AI, specifically text-to-image models, have revolutionized interior architectural design by enabling the rapid translation of conceptual ideas into visual representations from simple text prompts. While generative AI can produce…

Human-Computer Interaction · Computer Science 2025-06-19 Richa Gupta , Alexander Htet Kyaw
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