HunyuanWorld 1.0: Generating Immersive, Explorable, and Interactive 3D Worlds from Words or Pixels

• URL: http://arxiv.org/abs/2507.21809v1
• Date: Tue, 29 Jul 2025 13:43:35 GMT
• Title: HunyuanWorld 1.0: Generating Immersive, Explorable, and Interactive 3D Worlds from Words or Pixels
• Authors: HunyuanWorld Team, Zhenwei Wang, Yuhao Liu, Junta Wu, Zixiao Gu, Haoyuan Wang, Xuhui Zuo, Tianyu Huang, Wenhuan Li, Sheng Zhang, Yihang Lian, Yulin Tsai, Lifu Wang, Sicong Liu, Puhua Jiang, Xianghui Yang, Dongyuan Guo, Yixuan Tang, Xinyue Mao, Jiaao Yu, Junlin Yu, Jihong Zhang, Meng Chen, Liang Dong, Yiwen Jia, Chao Zhang, Yonghao Tan, Hao Zhang, Zheng Ye, Peng He, Runzhou Wu, Minghui Chen, Zhan Li, Wangchen Qin, Lei Wang, Yifu Sun, Lin Niu, Xiang Yuan, Xiaofeng Yang, Yingping He, Jie Xiao, Yangyu Tao, Jianchen Zhu, Jinbao Xue, Kai Liu, Chongqing Zhao, Xinming Wu, Tian Liu, Peng Chen, Di Wang, Yuhong Liu, Linus, Jie Jiang, Tengfei Wang, Chunchao Guo,
• Abstract summary: HunyuanWorld 1.0 is a novel framework that combines the best of both worlds for generating immersive, explorable, and interactive 3D scenes from text and image conditions.<n>Our approach features three key advantages: 1) 360deg immersive experiences via panoramic world proxies; 2) mesh export capabilities for seamless compatibility with existing computer graphics pipelines; 3) disentangled object representations for augmented interactivity.
• Score: 30.986527559921335
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Creating immersive and playable 3D worlds from texts or images remains a fundamental challenge in computer vision and graphics. Existing world generation approaches typically fall into two categories: video-based methods that offer rich diversity but lack 3D consistency and rendering efficiency, and 3D-based methods that provide geometric consistency but struggle with limited training data and memory-inefficient representations. To address these limitations, we present HunyuanWorld 1.0, a novel framework that combines the best of both worlds for generating immersive, explorable, and interactive 3D scenes from text and image conditions. Our approach features three key advantages: 1) 360{\deg} immersive experiences via panoramic world proxies; 2) mesh export capabilities for seamless compatibility with existing computer graphics pipelines; 3) disentangled object representations for augmented interactivity. The core of our framework is a semantically layered 3D mesh representation that leverages panoramic images as 360{\deg} world proxies for semantic-aware world decomposition and reconstruction, enabling the generation of diverse 3D worlds. Extensive experiments demonstrate that our method achieves state-of-the-art performance in generating coherent, explorable, and interactive 3D worlds while enabling versatile applications in virtual reality, physical simulation, game development, and interactive content creation.

Related papers

• WonderFree: Enhancing Novel View Quality and Cross-View Consistency for 3D Scene Exploration [28.97217489759405]
  Key challenge in current 3D generation methods is the limited explorability.<n>We propose WonderFree, the first model that enables users to interactively generate 3D worlds with the freedom to explore from arbitrary angles and directions.
  arXiv  Detail & Related papers  (2025-06-25T16:28:40Z)
• Voyager: Long-Range and World-Consistent Video Diffusion for Explorable 3D Scene Generation [66.95956271144982]
  We present Voyager, a novel video diffusion framework that generates world-consistent 3D point-cloud sequences from a single image.<n>Unlike existing approaches, Voyager achieves end-to-end scene generation and reconstruction with inherent consistency across frames.
  arXiv  Detail & Related papers  (2025-06-04T17:59:04Z)
• WorldExplorer: Towards Generating Fully Navigable 3D Scenes [49.21733308718443]
  WorldExplorer builds fully navigable 3D scenes with consistent visual quality across a wide range of viewpoints.<n>We generate multiple videos along short, pre-defined trajectories, that explore the scene in depth.<n>Our novel scene memory conditions each video on the most relevant prior views, while a collision-detection mechanism prevents degenerate results.
  arXiv  Detail & Related papers  (2025-06-02T15:41:31Z)
• Constructing a 3D Town from a Single Image [23.231661811526955]
  3DTown is a training-free framework designed to synthesize realistic and coherent 3D scenes from a single top-down view.<n>We decompose the input image into overlapping regions and generate each using a pretrained 3D object generator.<n>Our results demonstrate that high-quality 3D town generation is achievable from a single image using a principled, training-free approach.
  arXiv  Detail & Related papers  (2025-05-21T17:10:47Z)
• SynCity: Training-Free Generation of 3D Worlds [107.69875149880679]
  We propose SynCity, a training- and optimization-free approach to generating 3D worlds from textual descriptions.<n>We show how 3D and 2D generators can be combined to generate ever-expanding scenes.
  arXiv  Detail & Related papers  (2025-03-20T17:59:40Z)
• GenEx: Generating an Explorable World [59.0666303068111]
  We introduce GenEx, a system capable of planning complex embodied world exploration, guided by its generative imagination.<n>GenEx generates an entire 3D-consistent imaginative environment from as little as a single RGB image.<n> GPT-assisted agents are equipped to perform complex embodied tasks, including both goal-agnostic exploration and goal-driven navigation.
  arXiv  Detail & Related papers  (2024-12-12T18:59:57Z)
• WonderWorld: Interactive 3D Scene Generation from a Single Image [38.83667648993784]
  We present WonderWorld, a novel framework for interactive 3D scene generation.<n>WonderWorld generates connected and diverse 3D scenes in less than 10 seconds on a single A6000 GPU.
  arXiv  Detail & Related papers  (2024-06-13T17:59:10Z)
• 3D-SceneDreamer: Text-Driven 3D-Consistent Scene Generation [51.64796781728106]
  We propose a generative refinement network to synthesize new contents with higher quality by exploiting the natural image prior to 2D diffusion model and the global 3D information of the current scene. Our approach supports wide variety of scene generation and arbitrary camera trajectories with improved visual quality and 3D consistency.
  arXiv  Detail & Related papers  (2024-03-14T14:31:22Z)
• Unrolling Virtual Worlds for Immersive Experiences [13.615681132633561]
  This research pioneers a method for generating immersive worlds, drawing inspiration from elements of vintage adventure games like Myst. We explore the intricate conversion of 2D panoramas into 3D scenes using equirectangular projections.
  arXiv  Detail & Related papers  (2023-11-14T13:16:34Z)
• Sculpting Holistic 3D Representation in Contrastive Language-Image-3D Pre-training [51.632418297156605]
  We introduce MixCon3D, a method aiming to sculpt holistic 3D representation in contrastive language-image-3D pre-training. We develop the 3D object-level representation from complementary perspectives, e.g., multi-view rendered images with the point cloud. Then, MixCon3D performs language-3D contrastive learning, comprehensively depicting real-world 3D objects and bolstering text alignment.
  arXiv  Detail & Related papers  (2023-11-03T06:05:36Z)
• Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation [45.69270771487455]
  We propose a new method of Fantasia3D for high-quality text-to-3D content creation. Key to Fantasia3D is the disentangled modeling and learning of geometry and appearance. Our framework is more compatible with popular graphics engines, supporting relighting, editing, and physical simulation of the generated 3D assets.
  arXiv  Detail & Related papers  (2023-03-24T09:30:09Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.