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Procedural Content Generation (PCG) is the algorithmic generation of content, often applied to games. PCG and PCG via Machine Learning (PCGML) have appeared in published games. However, it can prove difficult to apply these approaches in…

Artificial Intelligence · Computer Science 2023-09-26 Emily Halina , Matthew Guzdial

The ability to automatically generate large-scale, interactive, and physically realistic 3D environments is crucial for advancing robotic learning and embodied intelligence. However, existing generative approaches often fail to capture the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 ChunTeng Chen , YiChen Hsu , YiWen Liu , WeiFang Sun , TsaiChing Ni , ChunYi Lee , Min Sun , YuanFu Yang

This paper proposes a novel framework for generating lingual descriptions of indoor scenes. Whereas substantial efforts have been made to tackle this problem, previous approaches focusing primarily on generating a single sentence for each…

Computer Vision and Pattern Recognition · Computer Science 2015-03-03 Dahua Lin , Chen Kong , Sanja Fidler , Raquel Urtasun

This paper introduces CameraCtrl II, a framework that enables large-scale dynamic scene exploration through a camera-controlled video diffusion model. Previous camera-conditioned video generative models suffer from diminished video dynamics…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Hao He , Ceyuan Yang , Shanchuan Lin , Yinghao Xu , Meng Wei , Liangke Gui , Qi Zhao , Gordon Wetzstein , Lu Jiang , Hongsheng Li

Traditional rendering pipelines rely on complex assets, accurate materials and lighting, and substantial computational resources to produce realistic imagery, yet they still face challenges in scalability and realism for populated dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Gonzalo Gomez-Nogales , Yicong Hong , Chongjian Ge , Peiye Zhuang , Marc Comino-Trinidad , Dan Casas , Yi Zhou

Procedural content generation via machine learning (PCGML) is the process of procedurally generating game content using models trained on existing game content. PCGML methods can struggle to capture the true variance present in underlying…

Machine Learning · Computer Science 2021-07-28 Bowei Li , Ruohan Chen , Yuqing Xue , Ricky Wang , Wenwen Li , Matthew Guzdial

Deep learning-based sketch-to-clothing image generation provides the initial designs and inspiration in the fashion design processes. However, clothing generation from freehand drawing is challenging due to the sparse and ambiguous…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Yongming Zhang , Tianyu Zhang , Haoran Xie

In Natural Language Processing (NLP), Large Language Models (LLMs) have demonstrated high text generation quality. However, in real-world applications, LLMs must meet increasingly complex requirements. Beyond avoiding misleading or…

Computation and Language · Computer Science 2024-08-23 Xun Liang , Hanyu Wang , Yezhaohui Wang , Shichao Song , Jiawei Yang , Simin Niu , Jie Hu , Dan Liu , Shunyu Yao , Feiyu Xiong , Zhiyu Li

Controllable scene generation could reduce the cost of diverse data collection substantially for autonomous driving. Prior works formulate the traffic layout generation as predictive progress, either by denoising entire sequences at once or…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Yunsong Zhou , Naisheng Ye , William Ljungbergh , Tianyu Li , Jiazhi Yang , Zetong Yang , Hongzi Zhu , Christoffer Petersson , Hongyang Li

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning. Specifically, we consider the problems of training a perception system to handle rare events,…

In this paper, we explore the task of generating expansive outdoor scenes, ranging from castles to high-rises. Unlike indoor scene generation, which has been a primary focus of prior work, outdoor scene generation presents unique…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Han-Hung Lee , Qinghong Han , Angel X. Chang

Procedural Content Generation (PCG) enables game content to be created algorithmically without direct manual level-design effort, but it introduces a serious evaluation problem: generated content may become unbalanced, blocked, repetitive,…

Artificial Intelligence · Computer Science 2026-05-05 Rishabh Kar

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

In the field of 3D content generation, single image scene reconstruction methods still struggle to simultaneously ensure the quality of individual assets and the coherence of the overall scene in complex environments, while texture editing…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

Generating high-quality and diverse human images is an important yet challenging task in vision and graphics. However, existing generative models often fall short under the high diversity of clothing shapes and textures. Furthermore, the…

Computer Vision and Pattern Recognition · Computer Science 2022-06-01 Yuming Jiang , Shuai Yang , Haonan Qiu , Wayne Wu , Chen Change Loy , Ziwei Liu

Our ability to sample realistic natural images, particularly faces, has advanced by leaps and bounds in recent years, yet our ability to exert fine-tuned control over the generative process has lagged behind. If this new technology is to…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Marek Kowalski , Stephan J. Garbin , Virginia Estellers , Tadas Baltrušaitis , Matthew Johnson , Jamie Shotton

Scene graphs offer a structured, hierarchical representation of images, with nodes and edges symbolizing objects and the relationships among them. It can serve as a natural interface for image editing, dramatically improving precision and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Zhiyuan Zhang , DongDong Chen , Jing Liao

Recently, there is a growing interest in creating computer-aided design (CAD) models based on user intent, known as controllable CAD generation. Existing work offers limited controllability and needs separate models for different types of…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Zhanwei Zhang , Shizhao Sun , Wenxiao Wang , Deng Cai , Jiang Bian

The generation of 3D scenes from user-specified conditions offers a promising avenue for alleviating the production burden in 3D applications. Previous studies required significant effort to realize the desired scene, owing to limited…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Takayuki Hara , Tatsuya Harada