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Related papers: Self-Evolving 3D Scene Generation from a Single Im…

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Recent single-view 3D generative methods have made significant advancements by leveraging knowledge distilled from extensive 3D object datasets. However, challenges persist in the synthesis of 3D scenes from a single view, primarily due to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Guo Pu , Yiming Zhao , Zhouhui Lian

As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident. In our work, we aim to train…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Jun Gao , Tianchang Shen , Zian Wang , Wenzheng Chen , Kangxue Yin , Daiqing Li , Or Litany , Zan Gojcic , Sanja Fidler

The scarcity of free-hand sketch presents a challenging problem. Despite the emergence of some large-scale sketch datasets, these datasets primarily consist of sketches at the single-object level. There continues to be a lack of large-scale…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zhenbei Wu , Qiang Wang , Jie Yang

Generative reconstruction methods compute the 3D configuration (such as pose and/or geometry) of a shape by optimizing the overlap of the projected 3D shape model with images. Proper handling of occlusions is a big challenge, since the…

Computer Vision and Pattern Recognition · Computer Science 2016-02-12 Helge Rhodin , Nadia Robertini , Christian Richardt , Hans-Peter Seidel , Christian Theobalt

Inverse graphics aims to recover 3D models from 2D observations. Utilizing differentiable rendering, recent 3D-aware generative models have shown impressive results of rigid object generation using 2D images. However, it remains challenging…

Computer Vision and Pattern Recognition · Computer Science 2022-10-11 Fangzhou Hong , Zhaoxi Chen , Yushi Lan , Liang Pan , Ziwei Liu

3D instance segmentation is fundamental to geometric understanding of the world around us. Existing methods for instance segmentation of 3D scenes rely on supervision from expensive, manual 3D annotations. We propose UnScene3D, the first…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 David Rozenberszki , Or Litany , Angela Dai

With recent developments in Embodied Artificial Intelligence (EAI) research, there has been a growing demand for high-quality, large-scale interactive scene generation. While prior methods in scene synthesis have prioritized the naturalness…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Yandan Yang , Baoxiong Jia , Peiyuan Zhi , Siyuan Huang

Synthesizing multi-view 3D from one single image is a significant but challenging task. Zero-1-to-3 methods have achieved great success by lifting a 2D latent diffusion model to the 3D scope. The target view image is generated with a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Yabo Chen , Jiemin Fang , Yuyang Huang , Taoran Yi , Xiaopeng Zhang , Lingxi Xie , Xinggang Wang , Wenrui Dai , Hongkai Xiong , Qi Tian

This paper introduces MIDI, a novel paradigm for compositional 3D scene generation from a single image. Unlike existing methods that rely on reconstruction or retrieval techniques or recent approaches that employ multi-stage…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Zehuan Huang , Yuan-Chen Guo , Xingqiao An , Yunhan Yang , Yangguang Li , Zi-Xin Zou , Ding Liang , Xihui Liu , Yan-Pei Cao , Lu Sheng

The vision-based semantic scene completion task aims to predict dense geometric and semantic 3D scene representations from 2D images. However, the presence of dynamic objects in the scene seriously affects the accuracy of the model…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Meng Wang , Fan Wu , Yunchuan Qin , Ruihui Li , Zhuo Tang , Kenli Li

Scene generation has extensive industrial applications, demanding both high realism and precise control over geometry and appearance. Language-driven retrieval methods compose plausible scenes from a large object database, but overlook…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Zhifei Yang , Guangyao Zhai , Keyang Lu , YuYang Yin , Chao Zhang , Zhen Xiao , Jieyi Long , Nassir Navab , Yikai Wang

Precise geometric control in image generation is essential for engineering \& product design and creative industries to control 3D object features accurately in image space. Traditional 3D editing approaches are time-consuming and demand…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Phillip Mueller , Talip Uenlue , Sebastian Schmidt , Marcel Kollovieh , Jiajie Fan , Stephan Guennemann , Lars Mikelsons

Automatic scene generation is an essential area of research with applications in robotics, recreation, visual representation, training and simulation, education, and more. This survey provides a comprehensive review of the current…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Awal Ahmed Fime , Saifuddin Mahmud , Arpita Das , Md. Sunzidul Islam , Hong-Hoon Kim

We present I2V3D, a novel framework for animating static images into dynamic videos with precise 3D control, leveraging the strengths of both 3D geometry guidance and advanced generative models. Our approach combines the precision of a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Zhiyuan Zhang , Dongdong Chen , Jing Liao

Egocentric human motion generation and forecasting with scene-context is crucial for enhancing AR/VR experiences, improving human-robot interaction, advancing assistive technologies, and enabling adaptive healthcare solutions by accurately…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Chaitanya Patel , Hiroki Nakamura , Yuta Kyuragi , Kazuki Kozuka , Juan Carlos Niebles , Ehsan Adeli

3D assets are essential in the digital age. While automatic 3D generation, such as image-to-3d, has made significant strides in recent years, it often struggles to achieve fast, detailed, and high-fidelity generation simultaneously. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Huanning Dong , Yinuo Huang , Fan Li , Ping Kuang

We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simulation to produce physically plausible, simulation-ready, and intersection-free 3D scenes.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Guying Lin , Kemeng Huang , Michael Liu , Ruihan Gao , Hanke Chen , Lyuhao Chen , Beijia Lu , Taku Komura , Yuan Liu , Jun-Yan Zhu , Minchen Li

Generating immersive 3D scenes from texts is a core task in computer vision, crucial for applications in virtual reality and game development. Despite the promise of leveraging 2D diffusion priors, existing methods suffer from spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Jisheng Chu , Wenrui Li , Rui Zhao , Wangmeng Zuo , Shifeng Chen , Xiaopeng Fan

Learning object-centric representations from unsupervised videos is challenging. Unlike most previous approaches that focus on decomposing 2D images, we present a 3D generative model named DynaVol-S for dynamic scenes that enables…

Computer Vision and Pattern Recognition · Computer Science 2025-02-17 Yanpeng Zhao , Yiwei Hao , Siyu Gao , Yunbo Wang , Xiaokang Yang

We present WonderWorld, a novel framework for interactive 3D scene generation that enables users to interactively specify scene contents and layout and see the created scenes in low latency. The major challenge lies in achieving fast…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Hong-Xing Yu , Haoyi Duan , Charles Herrmann , William T. Freeman , Jiajun Wu