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This paper addresses the challenge of object-centric layout generation under spatial constraints, seen in multiple domains including floorplan design process. The design process typically involves specifying a set of spatial constraints…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Mohammed Haroon Dupty , Yanfei Dong , Sicong Leng , Guoji Fu , Yong Liang Goh , Wei Lu , Wee Sun Lee

Despite the recent progress of generative adversarial networks (GANs) at synthesizing photo-realistic images, producing complex urban scenes remains a challenging problem. Previous works break down scene generation into two consecutive…

Computer Vision and Pattern Recognition · Computer Science 2021-06-04 Guillaume Le Moing , Tuan-Hung Vu , Himalaya Jain , Patrick Pérez , Matthieu Cord

Recent advancements in large language models have revolutionized text generation with their remarkable capabilities. These models can produce controlled texts that closely adhere to specific requirements when prompted appropriately.…

Computation and Language · Computer Science 2025-03-17 Zhe Yang , Yi Huang , Yaqin Chen , Xiaoting Wu , Junlan Feng , Chao Deng

Recent advances in latent diffusion models have demonstrated state-of-the-art performance in high-dimensional time-series data synthesis while providing flexible control through conditioning and guidance. However, existing methodologies…

Machine Learning · Computer Science 2025-11-11 Matteo Pettenó , Alessandro Ilic Mezza , Alberto Bernardini

Camouflaged image generation (CIG) has recently emerged as an efficient alternative for acquiring high-quality training data for camouflaged object detection (COD). However, existing CIG methods still suffer from a substantial gap to real…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Chunyuan Chen , Yunuo Cai , Shujuan Li , Weiyun Liang , Bin Wang , Jing Xu

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

Recent advances in large pre-trained language models have demonstrated strong results in generating natural languages and significantly improved performances for many natural language generation (NLG) applications such as machine…

Computation and Language · Computer Science 2022-09-27 Nanyun Peng

Controllable text generation concerns two fundamental tasks of wide applications, namely generating text of given attributes (i.e., attribute-conditional generation), and minimally editing existing text to possess desired attributes (i.e.,…

Computation and Language · Computer Science 2022-01-25 Zhiting Hu , Li Erran Li

Fashionable image generation aims to synthesize images of diverse fashion prevalent around the globe, helping fashion designers in real-time visualization by giving them a basic customized structure of how a specific design preference would…

Computer Vision and Pattern Recognition · Computer Science 2023-06-14 Krishna Sri Ipsit Mantri , Nevasini Sasikumar

Graphic design is ubiquitous in people's daily lives. For graphic design, the most time-consuming task is laying out various components in the interface. Repetitive manual layout design will waste a lot of time for professional graphic…

Human-Computer Interaction · Computer Science 2022-01-07 Mengxi Guo , Dangqing Huang , Xiaodong Xie

Conditional image generation has paved the way for several breakthroughs in image editing, generating stock photos and 3-D object generation. This continues to be a significant area of interest with the rise of new state-of-the-art methods…

Computer Vision and Pattern Recognition · Computer Science 2022-05-10 Vedant Singh , Surgan Jandial , Ayush Chopra , Siddharth Ramesh , Balaji Krishnamurthy , Vineeth N. Balasubramanian

Two fundamental challenges face generative models in engineering applications: the acquisition of high-performing, diverse datasets, and the adherence to precise constraints in generated designs. We propose a novel approach combining…

Neural and Evolutionary Computing · Computer Science 2024-05-17 Adam Gaier , James Stoddart , Lorenzo Villaggi , Shyam Sudhakaran

This study investigates human-computer interface generation based on diffusion models to overcome the limitations of traditional template-based design and fixed rule-driven methods. It first analyzes the key challenges of interface…

Human-Computer Interaction · Computer Science 2026-01-13 Rui Liu , Liuqingqing Yang , Runsheng Zhang , Shixiao Wang

With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video generation foundation models has led to growing demand for…

Deep generative neural networks have proven effective at both conditional and unconditional modeling of complex data distributions. Conditional generation enables interactive control, but creating new controls often requires expensive…

Machine Learning · Computer Science 2017-12-25 Jesse Engel , Matthew Hoffman , Adam Roberts

Foley sound generation aims to synthesise the background sound for multimedia content. Previous models usually employ a large development set with labels as input (e.g., single numbers or one-hot vector). In this work, we propose a…

Sound · Computer Science 2023-09-19 Yi Yuan , Haohe Liu , Xubo Liu , Xiyuan Kang , Peipei Wu , Mark D. Plumbley , Wenwu Wang

Recent advancements in generative AI have introduced novel prospects and practical implementations. Especially diffusion models show their strength in generating diverse and, at the same time, realistic features, positioning them well for…

Machine Learning · Computer Science 2024-06-05 Franz Motzkus , Christian Hellert , Ute Schmid

Recent advances in 3D generation have transitioned from multi-view 2D rendering approaches to 3D-native latent diffusion frameworks that exploit geometric priors in ground truth data. Despite progress, three key limitations persist: (1)…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Shaocong Dong , Lihe Ding , Xiao Chen , Yaokun Li , Yuxin Wang , Yucheng Wang , Qi Wang , Jaehyeok Kim , Chenjian Gao , Zhanpeng Huang , Zibin Wang , Tianfan Xue , Dan Xu

Document AI has advanced rapidly and is attracting increasing attention. Yet, while most efforts have focused on document layout analysis (DLA), its generative counterpart, layout generation, remains underexplored. Distinct from traditional…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Hengrui Kang , Zhuangcheng Gu , Zhiyuan Zhao , Zichen Wen , Bin Wang , Weijia Li , Conghui He

Recent advances in conditional generative image models have enabled impressive results. On the one hand, text-based conditional models have achieved remarkable generation quality, by leveraging large-scale datasets of image-text pairs. To…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Arantxa Casanova , Marlène Careil , Adriana Romero-Soriano , Christopher J. Pal , Jakob Verbeek , Michal Drozdzal