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Recent advancements in 3D generation have leveraged synthetic datasets with ground truth 3D assets and predefined cameras. However, the potential of adopting real-world datasets, which can produce significantly more realistic 3D scenes,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Xinyang Li , Zhangyu Lai , Linning Xu , Yansong Qu , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

We present RoboGen, a generative robotic agent that automatically learns diverse robotic skills at scale via generative simulation. RoboGen leverages the latest advancements in foundation and generative models. Instead of directly using or…

Language agents increasingly require persistent worlds in which they can act, remember, and learn. Existing approaches sit at two extremes: conventional web frameworks provide reliable but fixed contexts backed by databases, while fully…

Artificial Intelligence · Computer Science 2025-12-30 Jichen Feng , Yifan Zhang , Chenggong Zhang , Yifu Lu , Shilong Liu , Mengdi Wang

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

3D scene generation conditioned on text prompts has significantly progressed due to the development of 2D diffusion generation models. However, the textual description of 3D scenes is inherently inaccurate and lacks fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Minglin Chen , Longguang Wang , Sheng Ao , Ye Zhang , Kai Xu , Yulan Guo

Style-conditioned scene text generation faces unique challenges in extracting precise text styles from complex backgrounds and maintaining fine-grained style consistency across characters, especially for multilingual scripts. We propose…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Zeyu Chen , Fangmin Zhao , Yan Shu , Yichao Liu , Liu Yu , Yu Zhou

In this work, we propose a framework that creates a lively virtual dynamic scene with contextual motions of multiple humans. Generating multi-human contextual motion requires holistic reasoning over dynamic relationships among human-human…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Donggeun Lim , Jinseok Bae , Inwoo Hwang , Seungmin Lee , Hwanhee Lee , Young Min Kim

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. Additionally, 3D scene generation is vital for advancing embodied AI and world models, which depend…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yuxin Zhang , Ziyu Lu , Hongbo Duan , Keyu Fan , Pengting Luo , Peiyu Zhuang , Mengyu Yang , Houde Liu

Simulation plays a crucial role in the development of autonomous vehicles (AVs) due to the potential risks associated with real-world testing. Although significant progress has been made in the visual aspects of simulators, generating…

Machine Learning · Computer Science 2024-08-14 Wenhao Ding , Yulong Cao , Ding Zhao , Chaowei Xiao , Marco Pavone

We present WonderZoom, a novel approach to generating 3D scenes with contents across multiple spatial scales from a single image. Existing 3D world generation models remain limited to single-scale synthesis and cannot produce coherent scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Jin Cao , Hong-Xing Yu , Jiajun Wu

In this paper, we propose a novel controllable text-to-image generative adversarial network (ControlGAN), which can effectively synthesise high-quality images and also control parts of the image generation according to natural language…

Computer Vision and Pattern Recognition · Computer Science 2019-12-20 Bowen Li , Xiaojuan Qi , Thomas Lukasiewicz , Philip H. S. Torr

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun

We present EasyGen, an efficient model designed to enhance multimodal understanding and generation by harnessing the capabilities of diffusion models and large language models (LLMs), Unlike existing multimodal models that predominately…

Artificial Intelligence · Computer Science 2024-05-20 Xiangyu Zhao , Bo Liu , Qijiong Liu , Guangyuan Shi , Xiao-Ming Wu

Recent advances in diffusion models can generate high-quality and stunning images from text. However, multi-turn image generation, which is of high demand in real-world scenarios, still faces challenges in maintaining semantic consistency…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Junhao Cheng , Baiqiao Yin , Kaixin Cai , Minbin Huang , Hanhui Li , Yuxin He , Xi Lu , Yue Li , Yifei Li , Yuhao Cheng , Yiqiang Yan , Xiaodan Liang

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

We propose FlashWorld, a generative model that produces 3D scenes from a single image or text prompt in seconds, 10~100$\times$ faster than previous works while possessing superior rendering quality. Our approach shifts from the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinyang Li , Tengfei Wang , Zixiao Gu , Shengchuan Zhang , Chunchao Guo , Liujuan Cao

Large language models (LLMs) can help writers build story worlds by generating world elements, such as factions, characters, and locations. However, making sense of many generated elements can be overwhelming. Moreover, if the user wants to…

Human-Computer Interaction · Computer Science 2024-08-09 John Joon Young Chung , Max Kreminski

3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D object and scene generation, they still fall short of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Xingyi Li , Yizheng Wu , Jun Cen , Juewen Peng , Kewei Wang , Ke Xian , Zhe Wang , Zhiguo Cao , Guosheng Lin

In this work, we explore the challenging task of generating 3D shapes from text. Beyond the existing works, we propose a new approach for text-guided 3D shape generation, capable of producing high-fidelity shapes with colors that match the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhengzhe Liu , Yi Wang , Xiaojuan Qi , Chi-Wing Fu

Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains. While these methods have incrementally improved the generated image fidelity and text relevancy, several pivotal…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Oran Gafni , Adam Polyak , Oron Ashual , Shelly Sheynin , Devi Parikh , Yaniv Taigman