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---
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pretty_name: PhysInOne
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language:
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- en
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license: cc-by-nc-4.0
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modalities:
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- video
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- image
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- depth
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- segmentation
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- trajectory
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- pointcloud
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- text
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size_categories:
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- 1M<n<10M
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task_categories:
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- text-to-video
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- image-to-video
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- video-to-video
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- depth-estimation
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- image-segmentation
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- object-detection
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- other
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tags:
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- video
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- 3d
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- synthetic-data
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- physical-reasoning
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- visual-physics
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- world-model
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- video-generation
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- future-frame-prediction
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- physical-property-estimation
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- motion-transfer
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- multiview
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- simulation
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- embodied-ai
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- mechanics
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- optics
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- fluid-dynamics
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- magnetism
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- unreal-engine
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- mpm
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- sph
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arxiv: 2604.09415
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homepage: https://vlar-group.github.io/PhysInOne.html
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---
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<h1 align="center" style="font-size: 42px;">PhysInOne: Visual Physics Learning and Reasoning in One Suite</h1>
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<p align="center">
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Siyuan Zhou<sup>1†</sup>
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Hejun Wang<sup>1†</sup>
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Hu Cheng<sup>1†</sup>
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Jinxi Li<sup>1†</sup>
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Dongsheng Wang<sup>1†</sup>
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Junwei Jiang<sup>1†</sup> <br>
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Yixiao Jin<sup>1†</sup>
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Jiayue Huang<sup>1†</sup>
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Shiwei Mao<sup>1†</sup>
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Shangjia Liu<sup>2</sup>
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Yafei Yang<sup>1</sup> <br>
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Hongkang Song<sup>1</sup>
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Shenxing Wei<sup>1</sup>
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Zihui Zhang<sup>1</sup>
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DataTeam<sup>1*</sup>
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Bing Wang<sup>2</sup>
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Zhihua Wang<sup>3</sup>
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Chuhang Zou<sup>4</sup>
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Bo Yang<sup>1‡</sup>
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</p>
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<p align="center">
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<sup>1</sup> vLAR Group
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<sup>2</sup> The Hong Kong Polytechnic University
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<sup>3</sup> Syai Singapore
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<sup>4</sup> Meta
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</p>
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<p align="center">
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<sup>†</sup> Equal Contribution
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<sup>‡</sup> Corresponding Author
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</p>
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<p align="center">
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<sup>*</sup> {Peng Huang, Shijie Liu, Zhengli Hao, Hao Li, Yitian Li, Wenqi Zhou, Zhihan Zhao, Zongqi He, Hongtao Wen, Shouwang Huang, Peng Yun, Bowen Cheng, Pok Kazaf Fu, Wai Kit Lai, Jiahao Chen, Kaiyuan Wang, Zhixuan Sun, Ziqi Li, Haochen Hu, Di Zhang, Chun Ho Yuen}
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</p>
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<p align="center">
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<strong>CVPR 2026</strong>
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</p>
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<p align="center">
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<a href="https://vlar-group.github.io/PhysInOne.html">
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<img src="https://img.shields.io/badge/Project-Page-purple">
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</a>
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<a href="https://arxiv.org/abs/2604.09415">
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<img src="https://img.shields.io/badge/Paper-ArXiv-red">
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</a>
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<a href="TODO">
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<img src="https://img.shields.io/badge/Code-GitHub-black">
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</a>
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<a href="TODO">
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<img src="https://img.shields.io/badge/Dataset-HuggingFace-yellow">
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</a>
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<a href="TODO">
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<img src="https://img.shields.io/badge/Leaderboard-Coming_Soon-blue">
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</a>
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</p>
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| 1 |
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---
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pretty_name: PhysInOne
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+
language:
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| 4 |
+
- en
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| 5 |
+
license: cc-by-nc-4.0
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| 6 |
+
modalities:
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| 7 |
+
- video
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| 8 |
+
- image
|
| 9 |
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- depth
|
| 10 |
+
- segmentation
|
| 11 |
+
- trajectory
|
| 12 |
+
- pointcloud
|
| 13 |
+
- text
|
| 14 |
+
size_categories:
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| 15 |
+
- 1M<n<10M
|
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+
task_categories:
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| 17 |
+
- text-to-video
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| 18 |
+
- image-to-video
|
| 19 |
+
- video-to-video
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- depth-estimation
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| 21 |
+
- image-segmentation
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| 22 |
+
- object-detection
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| 23 |
+
- other
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tags:
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- video
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| 26 |
+
- 3d
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| 27 |
+
- synthetic-data
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+
- physical-reasoning
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- visual-physics
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- world-model
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- video-generation
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- future-frame-prediction
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| 33 |
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- physical-property-estimation
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+
- motion-transfer
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| 35 |
+
- multiview
|
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+
- simulation
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| 37 |
+
- embodied-ai
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| 38 |
+
- mechanics
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| 39 |
+
- optics
|
| 40 |
+
- fluid-dynamics
|
| 41 |
+
- magnetism
|
| 42 |
+
- unreal-engine
|
| 43 |
+
- mpm
|
| 44 |
+
- sph
|
| 45 |
+
arxiv: 2604.09415
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| 46 |
+
homepage: https://vlar-group.github.io/PhysInOne.html
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| 47 |
+
---
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| 48 |
+
|
| 49 |
+
<h1 align="center" style="font-size: 42px;">PhysInOne: Visual Physics Learning and Reasoning in One Suite</h1>
|
| 50 |
+
|
| 51 |
+
<p align="center">
|
| 52 |
+
Siyuan Zhou<sup>1†</sup>
|
| 53 |
+
Hejun Wang<sup>1†</sup>
|
| 54 |
+
Hu Cheng<sup>1†</sup>
|
| 55 |
+
Jinxi Li<sup>1†</sup>
|
| 56 |
+
Dongsheng Wang<sup>1†</sup>
|
| 57 |
+
Junwei Jiang<sup>1†</sup> <br>
|
| 58 |
+
Yixiao Jin<sup>1†</sup>
|
| 59 |
+
Jiayue Huang<sup>1†</sup>
|
| 60 |
+
Shiwei Mao<sup>1†</sup>
|
| 61 |
+
Shangjia Liu<sup>2</sup>
|
| 62 |
+
Yafei Yang<sup>1</sup> <br>
|
| 63 |
+
Hongkang Song<sup>1</sup>
|
| 64 |
+
Shenxing Wei<sup>1</sup>
|
| 65 |
+
Zihui Zhang<sup>1</sup>
|
| 66 |
+
DataTeam<sup>1*</sup>
|
| 67 |
+
Bing Wang<sup>2</sup>
|
| 68 |
+
Zhihua Wang<sup>3</sup>
|
| 69 |
+
Chuhang Zou<sup>4</sup>
|
| 70 |
+
Bo Yang<sup>1‡</sup>
|
| 71 |
+
</p>
|
| 72 |
+
|
| 73 |
+
<p align="center">
|
| 74 |
+
<sup>1</sup> vLAR Group
|
| 75 |
+
<sup>2</sup> The Hong Kong Polytechnic University
|
| 76 |
+
<sup>3</sup> Syai Singapore
|
| 77 |
+
<sup>4</sup> Meta
|
| 78 |
+
</p>
|
| 79 |
+
|
| 80 |
+
<p align="center">
|
| 81 |
+
<sup>†</sup> Equal Contribution
|
| 82 |
+
<sup>‡</sup> Corresponding Author
|
| 83 |
+
</p>
|
| 84 |
+
|
| 85 |
+
<p align="center">
|
| 86 |
+
<sup>*</sup> {Peng Huang, Shijie Liu, Zhengli Hao, Hao Li, Yitian Li, Wenqi Zhou, Zhihan Zhao, Zongqi He, Hongtao Wen, Shouwang Huang, Peng Yun, Bowen Cheng, Pok Kazaf Fu, Wai Kit Lai, Jiahao Chen, Kaiyuan Wang, Zhixuan Sun, Ziqi Li, Haochen Hu, Di Zhang, Chun Ho Yuen}
|
| 87 |
+
</p>
|
| 88 |
+
|
| 89 |
+
<p align="center">
|
| 90 |
+
<strong>CVPR 2026</strong>
|
| 91 |
+
</p>
|
| 92 |
+
|
| 93 |
+
<p align="center">
|
| 94 |
+
<a href="https://vlar-group.github.io/PhysInOne.html">
|
| 95 |
+
<img src="https://img.shields.io/badge/Project-Page-purple">
|
| 96 |
+
</a>
|
| 97 |
+
<a href="https://arxiv.org/abs/2604.09415">
|
| 98 |
+
<img src="https://img.shields.io/badge/Paper-ArXiv-red">
|
| 99 |
+
</a>
|
| 100 |
+
<a href="TODO">
|
| 101 |
+
<img src="https://img.shields.io/badge/Code-GitHub-black">
|
| 102 |
+
</a>
|
| 103 |
+
<a href="TODO">
|
| 104 |
+
<img src="https://img.shields.io/badge/Dataset-HuggingFace-yellow">
|
| 105 |
+
</a>
|
| 106 |
+
<a href="TODO">
|
| 107 |
+
<img src="https://img.shields.io/badge/Leaderboard-Coming_Soon-blue">
|
| 108 |
+
</a>
|
| 109 |
+
</p>
|
| 110 |
+
|
| 111 |
+
|
| 112 |
+
<div style="display: flex; align-items: flex-start; gap: 24px;">
|
| 113 |
+
|
| 114 |
+
<aside style="min-width: 220px; max-width: 240px; position: sticky; top: 16px; padding: 16px; border: 1px solid #e5e7eb; border-radius: 12px; background: #f9fafb; font-size: 14px; line-height: 1.9;">
|
| 115 |
+
<strong>🧭 Navigation</strong><br><br>
|
| 116 |
+
<a href="#summary">���� Summary</a><br>
|
| 117 |
+
<a href="#release-timetable">🚀 Release Timetable</a><br>
|
| 118 |
+
<a href="#how-to-use">📥 How to Use</a><br>
|
| 119 |
+
<a href="#visual-overview">🎬 Visual Overview</a><br>
|
| 120 |
+
<a href="#dataset-structure">📦 Dataset Structure</a><br>
|
| 121 |
+
<a href="#data-splits">📊 Data Splits</a><br>
|
| 122 |
+
<a href="#data-fields">🧩 Data Fields</a><br>
|
| 123 |
+
<a href="#annotation-details">📝 Annotation Details</a><br>
|
| 124 |
+
<a href="#supported-tasks">🧪 Supported Tasks and Benchmarks</a><br>
|
| 125 |
+
<a href="#license">📜 License</a><br>
|
| 126 |
+
<a href="#citation">📚 Citation</a><br>
|
| 127 |
+
<a href="#contact">📮 Contact</a><br>
|
| 128 |
+
</aside>
|
| 129 |
+
|
| 130 |
+
<main style="min-width: 0; flex: 1;">
|
| 131 |
+
|
| 132 |
+
<a id="summary"></a>
|
| 133 |
+
|
| 134 |
+
## 📌 Summary
|
| 135 |
+
|
| 136 |
+
**PhysInOne** is a large-scale synthetic dataset for visual physics learning and reasoning. It contains **153,810 dynamic 3D scenes** and **2 million annotated videos**, covering **71 basic physical phenomena** across four domains of everyday physics: **mechanics**, **optics**, **fluid dynamics**, and **magnetism**.
|
| 137 |
+
|
| 138 |
+
Each scene may contain multi-object and multi-physics interactions in complex 3D environments. PhysInOne provides rich annotations including RGB videos, depth maps, object masks, 3D trajectories, camera poses, object meshes, material properties, and textual descriptions.
|
| 139 |
+
|
| 140 |
+
The dataset is designed to support research on physics-aware video generation, future frame prediction, physical property estimation, motion transfer, physical reasoning, and world models.
|
| 141 |
+
|
| 142 |
+
<a id="release-timetable"></a>
|
| 143 |
+
|
| 144 |
+
## 🚀 Release Timetable
|
| 145 |
+
|
| 146 |
+
| Component | Progress | Status | Notes |
|
| 147 |
+
| --------------------- | ----------------------------- | ------------ | --------------------------------- |
|
| 148 |
+
| SubSet | `██████████`100% | Released | |
|
| 149 |
+
| Rendered Data - Train | `█░░░░░░░░░` 5%(5277/122,988) | In progress | Last updated: May 21 |
|
| 150 |
+
| Rendered Data - Test | `░░░░░░░░░░` 0%(0/15411) | In progress | |
|
| 151 |
+
| Rendered Data - Val | `░░░░░░░░░░` 1%(103/15411) | In progress | |
|
| 152 |
+
| 3D Assets | `░░░░░░░░░░` 0% | Not released | Expected around June |
|
| 153 |
+
| Leaderboard | `░░░░░░░░░░` 0% | Ongoing | Link will be added when available |
|
| 154 |
+
| Baseline code | `░░░░░░░░░░` 0% | Not released | Expected around June |
|
| 155 |
+
| Data processing | `░░░░░░░░░░` 0% | Not released | Expected around June |
|
| 156 |
+
|
| 157 |
+
Due to the large scale of PhysInOne, the rendered data and annotations are split across multiple Hugging Face repositories. Below is the list:
|
| 158 |
+
|
| 159 |
+
- **PhysInOneP01**: https://huggingface.co/datasets/PhysInOneP01/PhysInOneP01
|
| 160 |
+
|
| 161 |
+
For large-scale downloading and filtering, please refer to the **How to Use** section below.
|
| 162 |
+
|
| 163 |
+
<a id="how-to-use"></a>
|
| 164 |
+
|
| 165 |
+
## 📥 How to Use
|
| 166 |
+
|
| 167 |
+
PhysInOne is distributed across multiple Hugging Face dataset repositories because of its large scale. We provide two scripts for selecting and downloading cases:
|
| 168 |
+
|
| 169 |
+
- `filter_cases.py`: parses the case-to-repository assignment file and exports selected cases to JSON.
|
| 170 |
+
- `download.py`: downloads the selected case zip files from the corresponding Hugging Face shard repositories.
|
| 171 |
+
|
| 172 |
+
The scripts support selection by:
|
| 173 |
+
|
| 174 |
+
- **Split**: `train`, `val`, `test`
|
| 175 |
+
- **Activity complexity**: `single`, `double`, `triple`
|
| 176 |
+
- **Physical phenomenon abbreviation**: `MovingHitsFixed`, `FrictionStop`, `LiquidTension`, ..., `GranularFall`
|
| 177 |
+
- **Number of cases**: globally sample `N` cases after filtering
|
| 178 |
+
|
| 179 |
+
## 1. Prepare Metadata Files
|
| 180 |
+
|
| 181 |
+
Place the metadata files as follows:
|
| 182 |
+
|
| 183 |
+
```text
|
| 184 |
+
metadata/
|
| 185 |
+
repo_assignment.txt
|
| 186 |
+
repo_map.json
|
| 187 |
+
scripts/
|
| 188 |
+
filter_cases.py
|
| 189 |
+
download.py
|
| 190 |
+
```
|
| 191 |
+
|
| 192 |
+
`repo_assignment.txt` stores the uploaded case-to-part mapping. Each line should follow:
|
| 193 |
+
|
| 194 |
+
```text
|
| 195 |
+
<Game UE path> <part_id>
|
| 196 |
+
```
|
| 197 |
+
|
| 198 |
+
Example:
|
| 199 |
+
|
| 200 |
+
```text
|
| 201 |
+
/Game/PhysInOne/Scenes/Train/DoublePhysics/AccelConcaveSpin_AccelSurfaceSpin__bg070__K5ER39.AccelConcaveSpin_AccelSurfaceSpin__bg070__K5ER39 physinone_part1
|
| 202 |
+
```
|
| 203 |
+
|
| 204 |
+
`repo_map.json` maps each part to its Hugging Face repository ID:
|
| 205 |
+
|
| 206 |
+
```json
|
| 207 |
+
{
|
| 208 |
+
"physinone_part1": "PhysInOneP01/PhysInOneP01"
|
| 209 |
+
}
|
| 210 |
+
```
|
| 211 |
+
|
| 212 |
+
## 2. Install Dependencies
|
| 213 |
+
|
| 214 |
+
```bash
|
| 215 |
+
pip install huggingface_hub tqdm
|
| 216 |
+
```
|
| 217 |
+
|
| 218 |
+
## 3. Filter Cases
|
| 219 |
+
|
| 220 |
+
### Filter by split
|
| 221 |
+
|
| 222 |
+
```bash
|
| 223 |
+
python scripts/filter_cases.py \
|
| 224 |
+
--split train \
|
| 225 |
+
--output selected_cases.json
|
| 226 |
+
```
|
| 227 |
+
|
| 228 |
+
### Filter by split and activity complexity
|
| 229 |
+
|
| 230 |
+
```bash
|
| 231 |
+
python scripts/filter_cases.py \
|
| 232 |
+
--split train \
|
| 233 |
+
--activity_type double \
|
| 234 |
+
--output selected_cases.json
|
| 235 |
+
```
|
| 236 |
+
|
| 237 |
+
### Filter by physical phenomenon abbreviation
|
| 238 |
+
|
| 239 |
+
By default, phenomenon matching uses `contains` mode. For example, the following command selects all double-physics cases that contain `FrictionStop`:
|
| 240 |
+
|
| 241 |
+
```bash
|
| 242 |
+
python scripts/filter_cases.py \
|
| 243 |
+
--split train \
|
| 244 |
+
--activity_type double \
|
| 245 |
+
--phenomena FrictionStop \
|
| 246 |
+
--match_mode contains \
|
| 247 |
+
--output selected_cases.json
|
| 248 |
+
```
|
| 249 |
+
|
| 250 |
+
For exact matching, use `--match_mode exact`. Order does not matter. For example, this command selects cases whose phenomenon set is exactly `{AccelConcaveSpin, AccelSurfaceSpin}`:
|
| 251 |
+
|
| 252 |
+
```bash
|
| 253 |
+
python scripts/filter_cases.py \
|
| 254 |
+
--split train \
|
| 255 |
+
--activity_type double \
|
| 256 |
+
--phenomena AccelConcaveSpin AccelSurfaceSpin \
|
| 257 |
+
--match_mode exact \
|
| 258 |
+
--output selected_cases.json
|
| 259 |
+
```
|
| 260 |
+
|
| 261 |
+
### Randomly sample a fixed number of cases
|
| 262 |
+
|
| 263 |
+
`--num` is the global number of cases sampled after filtering. The default random seed is `42`.
|
| 264 |
+
|
| 265 |
+
```bash
|
| 266 |
+
python scripts/filter_cases.py \
|
| 267 |
+
--split train \
|
| 268 |
+
--activity_type double \
|
| 269 |
+
--phenomena FrictionStop \
|
| 270 |
+
--match_mode contains \
|
| 271 |
+
--num 3000 \
|
| 272 |
+
--seed 42 \
|
| 273 |
+
--output selected_cases.json
|
| 274 |
+
```
|
| 275 |
+
|
| 276 |
+
## 4. Download Selected Cases
|
| 277 |
+
|
| 278 |
+
Each selected case is downloaded as a zip file from the corresponding Hugging Face shard repository.
|
| 279 |
+
|
| 280 |
+
```bash
|
| 281 |
+
python scripts/download.py \
|
| 282 |
+
--selection selected_cases.json \
|
| 283 |
+
--output_dir ./PhysInOne
|
| 284 |
+
```
|
| 285 |
+
|
| 286 |
+
If the dataset repositories are gated or private, pass a Hugging Face token:
|
| 287 |
+
|
| 288 |
+
```bash
|
| 289 |
+
python scripts/download.py \
|
| 290 |
+
--selection selected_cases.json \
|
| 291 |
+
--output_dir ./PhysInOne \
|
| 292 |
+
--token YOUR_HF_TOKEN
|
| 293 |
+
```
|
| 294 |
+
|
| 295 |
+
Preview the planned downloads without actually downloading files:
|
| 296 |
+
|
| 297 |
+
```bash
|
| 298 |
+
python scripts/download.py \
|
| 299 |
+
--selection selected_cases.json \
|
| 300 |
+
--dry_run
|
| 301 |
+
```
|
| 302 |
+
|
| 303 |
+
By default, downloaded zip files are saved into a flat output folder. To preserve shard/split/activity structure:
|
| 304 |
+
|
| 305 |
+
```bash
|
| 306 |
+
python scripts/download.py \
|
| 307 |
+
--selection selected_cases.json \
|
| 308 |
+
--output_dir ./PhysInOne \
|
| 309 |
+
--keep_shard_structure
|
| 310 |
+
```
|
| 311 |
+
|
| 312 |
+
The preserved structure is:
|
| 313 |
+
|
| 314 |
+
```text
|
| 315 |
+
PhysInOne/
|
| 316 |
+
physinone_part1/
|
| 317 |
+
Train/
|
| 318 |
+
DoublePhysics/
|
| 319 |
+
AccelConcaveSpin_AccelSurfaceSpin__bg070__K5ER39_trajectory.zip
|
| 320 |
+
```
|
| 321 |
+
|
| 322 |
+
<a id="visual-overview"></a>
|
| 323 |
+
|
| 324 |
+
## 🎬 Visual Overview
|
| 325 |
+
|
| 326 |
+
<p align="center">
|
| 327 |
+
<img src="assets/teaser.png" width="900">
|
| 328 |
+
</p>
|
| 329 |
+
|
| 330 |
+
For more examples, please visit our [homepage](https://vlar-group.github.io/PhysInOne.html).
|
| 331 |
+
|
| 332 |
+
<a id="dataset-structure"></a>
|
| 333 |
+
|
| 334 |
+
## 📦 Dataset Structure
|
| 335 |
+
|
| 336 |
+
TODO
|
| 337 |
+
|
| 338 |
+
<a id="data-splits"></a>
|
| 339 |
+
|
| 340 |
+
## 📊 Data Splits
|
| 341 |
+
|
| 342 |
+
PhysInOne is divided into three primary splits: **Train**, **Val**, and **Test**.
|
| 343 |
+
|
| 344 |
+
- **Train Split**: contains 122,988 scenes.
|
| 345 |
+
- **Validation Split**: contains 15,411 scenes.
|
| 346 |
+
- **Test Split**: contains 15,411 scenes.
|
| 347 |
+
|
| 348 |
+
Each split is generated using **completely distinct 3D meshes, and backgrounds** to ensure that models cannot overfit to shared geometry or scene layout across splits. No scene is repeated between splits, and objects, lighting, and environment setups are independent for each split.
|
| 349 |
+
|
| 350 |
+
This design guarantees that training, validation, and test sets are fully separated in terms of visual content and scene composition, providing a robust benchmark for generalization and physical reasoning tasks.
|
| 351 |
+
|
| 352 |
+
<a id="data-fields"></a>
|
| 353 |
+
|
| 354 |
+
## 🧩 Data Fields
|
| 355 |
+
|
| 356 |
+
### Physical Phenomenon and Abbreviations
|
| 357 |
+
|
| 358 |
+
<details>
|
| 359 |
+
<summary>Click to expand full abbreviation table</summary>
|
| 360 |
+
|
| 361 |
+
| ID | Physical Phenomenon | Abbreviation | Related Physical Laws |
|
| 362 |
+
| ----- | ------------------------------------------------------------------------- | --------------------- | ------------------------------------------------------- |
|
| 363 |
+
| `P01` | Object collide with static, stationary objects | MovingHitsFixed | Laws of Momentum |
|
| 364 |
+
| `P02` | Moving objects collide with non-static stationary objects | MovingHitsStationary | Laws of Momentum |
|
| 365 |
+
| `P03` | Two moving objects collide | MovingHitsMoving | Laws of Momentum |
|
| 366 |
+
| `P04` | Objects in equilibrium of wind and gravity | WindGravityBalance | Equilibrium, Aerodynamics, Gravity |
|
| 367 |
+
| `P05` | Wind applied to a stationary object | WindPushStationary | Aerodynamics |
|
| 368 |
+
| `P06` | Wind applied to objects moving in same direction | WindPushSameDir | Aerodynamics |
|
| 369 |
+
| `P07` | Wind applied to objects moving in the opposite direction | WindPushOppDir | Aerodynamics |
|
| 370 |
+
| `P08` | Wind applied to moving objects changes its velocity (applied at an angle) | WindDeflectMotion | Aerodynamics |
|
| 371 |
+
| `P09` | Object thrown up with angle | ObliqueProjectile | Gravity |
|
| 372 |
+
| `P10` | Objects falling straight down | VerticalFall | Gravity |
|
| 373 |
+
| `P11` | Objects rolling down a straight slope | RollDownSlope | Gravity, Friction |
|
| 374 |
+
| `P12` | Objects rolling up a slope | RollUpSlope | Gravity, Friction |
|
| 375 |
+
| `P13` | Magnetic Attraction | MagnetAttract | Magnetism |
|
| 376 |
+
| `P14` | Magnetic Repulsion | MagnetRepel | Magnetism |
|
| 377 |
+
| `P15` | Objects near uniformly rotating pillar | UniformPanelSpin | Laws of Rotation |
|
| 378 |
+
| `P16` | Objects near acceleratingly rotating pillar | AccelPanelSpin | Laws of Rotation |
|
| 379 |
+
| `P17` | Objects inside uniformly rotating bowl | UniformConcaveSpin | Equilibrium, Laws of Rotation, Gravity, Friction |
|
| 380 |
+
| `P18` | Objects inside acceleratingly rotating bowl | AccelConcaveSpin | Equilibrium, Laws of Rotation, Gravity, Friction |
|
| 381 |
+
| `P19` | Objects on uniformly rotating plane | UniformSurfaceSpin | Laws of Rotation, Friction |
|
| 382 |
+
| `P20` | Objects on acceleratingly rotating plane | AccelSurfaceSpin | Laws of Rotation, Friction |
|
| 383 |
+
| `P21` | Objects on coarse surface with friction | FrictionStop | Friction |
|
| 384 |
+
| `P22` | Spring is compressed | SpringCompress | Laws of Elasticity |
|
| 385 |
+
| `P23` | Spring is stretched | SpringStretch | Laws of Elasticity |
|
| 386 |
+
| `P24` | Breakable object shatters | ImpactFracture | Laws of Plasticity |
|
| 387 |
+
| `P25` | Mirror shatters | MirrorFragmentReflect | Laws of Plasticity, Law of Reflection |
|
| 388 |
+
| `P26` | Elastic rope connection | ElasticCouple | Laws of Elasticity |
|
| 389 |
+
| `P27` | Object bounces off spring board | SpringboardRebound | Laws of Elasticity, Laws of Momentum |
|
| 390 |
+
| `P28` | Objects interact with a balanced seesaw | SeesawCenterPivot | Laws of Torque |
|
| 391 |
+
| `P29` | Objects interact with an imbalanced seesaw | SeesawOffsetPivot | Laws of Torque |
|
| 392 |
+
| `P30` | Free balloon floats to ceiling | BalloonFloat | Laws of Buoyancy |
|
| 393 |
+
| `P31` | Tethered balloon pulls string taut | BalloonTether | Laws of Buoyancy, Rope Restraint |
|
| 394 |
+
| `P32` | Multiple balloons lifting | BalloonLift | Laws of Buoyancy, Rope Restraint, Gravity |
|
| 395 |
+
| `P33` | Laser hits flat mirror and reflects | FixedPlanarRedirect | Law of Reflection |
|
| 396 |
+
| `P34` | Laser reflects off multiple mirrors | FixedArrayRedirect | Law of Reflection |
|
| 397 |
+
| `P35` | Laser hits and reflects off concave mirror | FixedConcaveRedirect | Law of Reflection |
|
| 398 |
+
| `P36` | Laser hits and reflects off convex mirror | FixedConvexRedirect | Law of Reflection |
|
| 399 |
+
| `P37` | Mirror sweeps beam | DynMirrorRedirect | Law of Reflection |
|
| 400 |
+
| `P38` | Laser blocked by object | LaserBlock | Light Obstruction |
|
| 401 |
+
| `P39` | Mirror reflection | MirrorReflect | Law of Reflection |
|
| 402 |
+
| `P40` | Cart moving forward with rolling wheels | CartMove | Complex Mechanical Structure Constraints |
|
| 403 |
+
| `P41` | Objects on rotating turntable flies off | RotTurnableInertia | Laws of Rotation, Friction, Laws of Inertia |
|
| 404 |
+
| `P42` | Rotating block pushes another objects | RotBoardInertia | Laws of Inertia, Laws of Rotation, Laws of Momentum |
|
| 405 |
+
| `P43` | One object carrying another | LinCarryInertia | Laws of Inertia, Friction |
|
| 406 |
+
| `P44` | Catapult launches objects | CatapultLaunch | Special Mechanical Structure, Gravity |
|
| 407 |
+
| `P45` | Chain suspends objects | ChainSuspend | Complex Mechanical Structure Constraints, Gravity |
|
| 408 |
+
| `P46` | Objects Swing | SimplePendulum | Laws of Pendulum Motion, Gravity |
|
| 409 |
+
| `P47` | Double Pendulum Moves | DoublePendulum | Laws of Multiple Pendulum Motion, Gravity |
|
| 410 |
+
| `P48` | Crank push objects | CrankPush | Special Mechanical Structure |
|
| 411 |
+
| `P49` | Wall composed of square blocks collapses | BlockWallCollapse | Gravity, Structural Stability |
|
| 412 |
+
| `P50` | Wooden board supported by sticks collapses | StickSupportFail | Gravity, Structural Stability |
|
| 413 |
+
| `P51` | Objects float on the fluid surface | FloatOnLiquid | Laws of Buoyancy, Fluid Dynamics |
|
| 414 |
+
| `P52` | Objects drop into the fluid | DropInLiquid | Laws of Buoyancy, Fluid Dynamics |
|
| 415 |
+
| `P53` | Objects' movement causes fluid motion | MovingObjDriveLiquid | Fluid Dynamics |
|
| 416 |
+
| `P54` | Flowing fluid carries objects along | LiquidCarryMovingObj | Laws of Buoyancy, Fluid Dynamics |
|
| 417 |
+
| `P55` | Fluid flows against stationary objects | LiquidHitFixedObj | Fluid Dynamics |
|
| 418 |
+
| `P56` | Fluid transfers from one container to another | LiquidTransfer | Fluid Dynamics, Conservation of Mass, Surface Tension |
|
| 419 |
+
| `P57` | Fluid passes through several connected containers | LiquidMultiTransfers | Fluid Dynamics, Conservation of Mass, Surface Tension |
|
| 420 |
+
| `P58` | Fluid flows through grid-like structures | LiquidThroughGrid | Fluid Dynamics, Conservation of Mass |
|
| 421 |
+
| `P59` | Fluid moves across mountainous or uneven landscapes | LiquidAcrossUneven | Fluid Dynamics |
|
| 422 |
+
| `P60` | Increasing fluid volume elevates the surface level | LiquidRise | Fluid Dynamics |
|
| 423 |
+
| `P61` | Fluid flows along the contours of an object's surface | LiquidAlongContours | Fluid Dynamics |
|
| 424 |
+
| `P62` | Jet-like fluid projection upward or outward | JetLiquid | Fluid Dynamics |
|
| 425 |
+
| `P63` | Fluid exhibits surface tension | LiquidTension | Fluid Dynamics, Laws of Surface Tension |
|
| 426 |
+
| `P64` | Fluid refracts light when crossing media | LiquidRefraction | Fluid Dynamics, Optics, Law of Refraction (Snell's Law) |
|
| 427 |
+
| `P65` | Sticky fluid drips and accumulates on objects | StickyToObjects | Laws of Cohesion, Viscous Flow |
|
| 428 |
+
| `P66` | Sticky fluid falls from an object's surface | StickyFromObjects | Laws of Cohesion, Laws of Viscous Flow (Navier-Stokes) |
|
| 429 |
+
| `P67` | An elastic object falls and bounces on another surface | ElasticFall | Laws of Elasticity |
|
| 430 |
+
| `P68` | A plasticine object falls and deforms on a surface | PlasticineFall | Laws of Plasticity |
|
| 431 |
+
| `P69` | A Newtonian fluid falls and spreads across a surface | NewtonianFluidFall | Laws of Viscous Flow (Navier-Stokes) |
|
| 432 |
+
| `P70` | A Non-Newtonian fluid falls and flows with variable resistance | NonNewtonianFluidFall | Laws of Viscoplastics Flow |
|
| 433 |
+
| `P71` | A granular substance falls and disperses across a surface | GranularFall | Laws of Friction |
|
| 434 |
+
|
| 435 |
+
</details>
|
| 436 |
+
|
| 437 |
+
Example: **MovingHitsStationary_WindDeflectMotion_BalloonFloat__bg140__TZlWl1**
|
| 438 |
+
|
| 439 |
+
- The **first three components** correspond to specific physical phenomenon abbreviations (see table above).
|
| 440 |
+
- `bg140` indicates that the scene uses background number 140.
|
| 441 |
+
- The **last six-character string** (`TZlWl1`) is a unique hash code generated for this scene to guarantee uniqueness.
|
| 442 |
+
|
| 443 |
+
This naming convention allows users to quickly parse scene metadata and link it to the corresponding physical phenomena, background, and unique identifier.
|
| 444 |
+
|
| 445 |
+
<a id="annotation-details"></a>
|
| 446 |
+
|
| 447 |
+
## 📝 Annotation Details
|
| 448 |
+
|
| 449 |
+
PhysInOne provides synchronized visual and physical annotations for each dynamic 3D scene.
|
| 450 |
+
|
| 451 |
+
### Depth
|
| 452 |
+
|
| 453 |
+
Depth maps are provided in `.npz` format and are expressed in meters.
|
| 454 |
+
|
| 455 |
+
### Segmentation
|
| 456 |
+
|
| 457 |
+
Segmentation masks encode background, static foreground objects, and dynamic foreground objects.
|
| 458 |
+
|
| 459 |
+
Expected encoding:
|
| 460 |
+
|
| 461 |
+
| Pixel Value | Meaning |
|
| 462 |
+
| -----------:| -------------------------- |
|
| 463 |
+
| `0` | Background |
|
| 464 |
+
| `1-127` | Static foreground objects |
|
| 465 |
+
| `128-255` | Dynamic foreground objects |
|
| 466 |
+
|
| 467 |
+
### Captions
|
| 468 |
+
|
| 469 |
+
Each scene includes a `caption.txt` file containing an English paragraph that describes the visual elements and the physical activity.
|
| 470 |
+
|
| 471 |
+
### Trajectories
|
| 472 |
+
|
| 473 |
+
TODO
|
| 474 |
+
|
| 475 |
+
### Cameras
|
| 476 |
+
|
| 477 |
+
Each scene includes multiple camera viewpoints to support 3D perception, reconstruction, and physics-based visual reasoning tasks.
|
| 478 |
+
|
| 479 |
+
- **Taichi-based MPM simulations** (elastic solids, plasticine, granular substances, some Newtonian and Non-Newtonian fluids): 15 static cameras + 1 dynamic camera
|
| 480 |
+
- **Other scenes**: 12 static cameras + 1 dynamic camera
|
| 481 |
+
|
| 482 |
+
**Camera JSON structure** (per camera):
|
| 483 |
+
|
| 484 |
+
- `frames`: list of per-frame 4×4 camera-to-world (C2W) transformation matrices in **Blender coordinate system**
|
| 485 |
+
- `camera_angle_x`: horizontal field of view (FOV) in radians, can be used to compute intrinsic focal length
|
| 486 |
+
- `img_w`, `img_h`: image width and height in pixels
|
| 487 |
+
- `trajectory_name`: name of the camera trajectory
|
| 488 |
+
- `total_frames`, `fps`: number of frames and frames per second
|
| 489 |
+
|
| 490 |
+
**Dynamic camera behavior**:
|
| 491 |
+
|
| 492 |
+
- The dynamic camera moves along a path randomly sampled on a hemisphere surrounding the center of the main objects, providing diverse viewpoints.
|
| 493 |
+
- JSON frame indices correspond directly to video frame indices.
|
| 494 |
+
|
| 495 |
+
### Point Clouds
|
| 496 |
+
|
| 497 |
+
Each scene should include `points.ply`.
|
| 498 |
+
|
| 499 |
+
The initial point cloud was obtained by back-projecting the pixels from each camera view in the first frame based on depth, followed by randomly sampling 100,000 points from the resulting data.
|
| 500 |
+
|
| 501 |
+
<a id="supported-tasks"></a>
|
| 502 |
+
|
| 503 |
+
## 🧪 Supported Tasks and Benchmarks
|
| 504 |
+
|
| 505 |
+
PhysInOne supports the following visual physics learning and reasoning tasks.
|
| 506 |
+
|
| 507 |
+
- Physics-aware Video Generation
|
| 508 |
+
|
| 509 |
+
- Long-term and Short-term Future Frame Prediction
|
| 510 |
+
|
| 511 |
+
- Physical Property Estimation
|
| 512 |
+
|
| 513 |
+
- Motion Transfer
|
| 514 |
+
|
| 515 |
+
<a id="license"></a>
|
| 516 |
+
|
| 517 |
+
## 📜 License
|
| 518 |
+
|
| 519 |
+
All 3D assets and materials included in PhysInOne have been sourced from publicly available platforms and verified to carry licenses compatible with non-commercial use. These include:
|
| 520 |
+
|
| 521 |
+
- **SketchFab**: assets under various licenses, verified that AI-related usage is allowed.
|
| 522 |
+
- **Fab**: assets under CC BY or Unreal Engine Standard License, explicitly permitting AI-related usage.
|
| 523 |
+
- **BlenderKit**: distributed under Royalty-Free (RF) license.
|
| 524 |
+
- **ShareTextures**: textures under CC0 license.
|
| 525 |
+
|
| 526 |
+
In total, assets comply with licenses including **CC BY-NC, CC BY-SA, CC BY-NC-SA, CC0, CC BY, and RF**, ensuring all files can be legally used for building a non-commercial dataset. Users must adhere to the original licenses for any redistribution or derivative work.
|
| 527 |
+
|
| 528 |
+
> ⚠️ Note: PhysInOne is intended for **non-commercial research and educational purposes**. For commercial use, users must verify the licensing terms of individual assets.
|
| 529 |
+
|
| 530 |
+
<a id="citation"></a>
|
| 531 |
+
|
| 532 |
+
## 📚 Citation
|
| 533 |
+
|
| 534 |
+
If you use PhysInOne in your research, please cite:
|
| 535 |
+
|
| 536 |
+
```bibtex
|
| 537 |
+
@article{zhou2026physinone,
|
| 538 |
+
title={PhysInOne: Visual Physics Learning and Reasoning in One Suite},
|
| 539 |
+
author={Zhou, Siyuan and Wang, Hejun and Cheng, Hu and Li, Jinxi and Wang, Dongsheng and Jiang, Junwei and Jin, Yixiao and Huang, Jiayue and Mao, Shiwei and Liu, Shangjia and others},
|
| 540 |
+
journal={arXiv preprint arXiv:2604.09415},
|
| 541 |
+
year={2026}
|
| 542 |
+
}
|
| 543 |
+
```
|
| 544 |
+
|
| 545 |
+
<a id="contact"></a>
|
| 546 |
+
|
| 547 |
+
## 📮 Contact
|
| 548 |
+
|
| 549 |
+
For questions about the dataset, please contact:
|
| 550 |
+
|
| 551 |
+
- {siyuan.zhou, hejun.wang, hu123.cheng, jinxi.li}@connect.polyu.hk, bo.yang@polyu.edu.hk
|
| 552 |
+
|
| 553 |
+
|
| 554 |
+
</main>
|
| 555 |
+
</div>
|