📌 Summary

PhysInOne is a large-scale synthetic dataset for visual physics learning and reasoning, containing 153,810 dynamic 3D scenes and 2 million annotated videos across 71 physical phenomena in mechanics, optics, fluid dynamics, and magnetism. Each scene features complex multi-object and multi-physics interactions with rich annotations, including RGB videos, depth maps, object masks, 3D trajectories, camera poses, object meshes, material properties, and textual descriptions. The dataset supports research on physics-aware video generation, future frame prediction, physical property estimation, motion transfer, physical reasoning, and world models.

153,810
Dynamic 3D scenes

2M
Annotated videos

71
Physical phenomena

4
Physics domains

🚀 Release Timetable

| Component | Progress | Status | Notes | | --------------------- | ----------------------------- | ------------ | --------------------------------- | | SubSet | `██████████`100% | Released | | | Rendered Data - Train | `████████░░` 82%(101277/122,988) | In progress | Last updated: Jul 9 | | Rendered Data - Test | `░░░░░░░░░░` 0%(0/15411) | In progress | | | Rendered Data - Val | `░░░░░░░░░░` 1%(103/15411) | In progress | | | 3D Assets | `░░░░░░░░░░` 0% | Not released | Expected around July | | Leaderboard | `░░░░░░░░░░` 0% | Ongoing | Link will be added when available | | PMF | `██████████`100% | Released | | | Baselines | `░░░░░░░░░░` 0% | Not released | Expected around July | | Data processing | `░░░░░░░░░░` 0% | Not released | Expected around July | Due to the large scale of PhysInOne, the rendered data and annotations are split across multiple Hugging Face repositories. Below is the list: - PhysInOneP01: https://huggingface.co/datasets/PhysInOneP01/PhysInOneP01 4.48 TB - PhysInOneP02: https://huggingface.co/datasets/PhysInOneP02/PhysInOneP02 7.04 TB - PhysInOneP03: https://huggingface.co/datasets/PhysInOneP03/PhysInOneP03 7.55 TB - PhysInOneP04: https://huggingface.co/datasets/PhysInOneP04/PhysInOneP04 7.55 TB - PhysInOneP05: https://huggingface.co/datasets/PhysInOneP05/PhysInOneP05 7.13 TB - PhysInOneP06: https://huggingface.co/datasets/PhysInOneP06/PhysInOneP06 7.16 TB - PhysInOneP07: https://huggingface.co/datasets/PhysInOneP07/PhysInOneP07 7.17 TB - PhysInOneP08: https://huggingface.co/datasets/PhysInOneP08/PhysInOneP08 7.18 TB - PhysInOneP09: https://huggingface.co/datasets/PhysInOneP09/PhysInOneP09 7.16 TB - PhysInOneP10: https://huggingface.co/datasets/PhysInOneP10/PhysInOneP10 7.20 TB - PhysInOneP11: https://huggingface.co/datasets/PhysInOneP11/PhysInOneP11 6.13 TB - PhysInOneP12: https://huggingface.co/datasets/PhysInOneP12/PhysInOneP12 6.62 TB - PhysInOneP13: https://huggingface.co/datasets/PhysInOneP13/PhysInOneP13 6.62 TB - PhysInOneP14: https://huggingface.co/datasets/PhysInOneP14/PhysInOneP14 0.00 TB For large-scale downloading and filtering, please refer to the **How to Download** section below.

📊 Data Splits

PhysInOne is divided into Train, Val, and Test splits, containing 122,988, 15,411, and 15,411 scenes, respectively. The three splits are generated with completely distinct 3D meshes and backgrounds, ensuring that no scene or visual content is shared across splits. This separation provides a robust benchmark for evaluating generalization and physical reasoning.

📥 How to Download

1. Download Scripts

Please download the `assets` folder, which contains: ```text metadata/ repo_assignment.txt repo_map.json scripts/ filter_cases.py download.py ``` PhysInOne is distributed across multiple Hugging Face dataset repositories because of its large scale. We provide two scripts for selecting and downloading cases: - `filter_cases.py`: exports selected cases to JSON. - `download.py`: downloads the selected case zip files from the corresponding repositories.

2. Install Dependencies

```bash pip install huggingface_hub tqdm ```

3. Filter Cases

Export a JSON file containing case information matching your filter criteria, for use in subsequent download scripts. The `filter_cases.py` script supports selection by: - Split: `train`, `val`, `test` - Activity complexity: `single`, `double`, `triple` - Physical phenomenon abbreviation: `MovingHitsFixed`, `FrictionStop`, `LiquidTension`, ..., `GranularFall` - Number of cases: globally sample `num` cases after filtering The following examples show common filtering workflows.

3.1 Filter by split

```bash python scripts/filter_cases.py \ --split train \ --output selected_cases.json ```

3.2 Filter by split and activity complexity

```bash python scripts/filter_cases.py \ --split train \ --activity_type double \ --output selected_cases.json ```

3.3 Filter by physical phenomenon abbreviation

By default, phenomenon matching uses `contains` mode. For example, the following command selects all double-physics cases that contain `FrictionStop`(For all physical phenomena and their abbreviations, please refer to the **Data Fields** section below.): ```bash python scripts/filter_cases.py \ --split train \ --activity_type double \ --phenomena FrictionStop \ --match_mode contains \ --output selected_cases.json ``` For exact matching, use `--match_mode exact`. Order does not matter. For example, this command selects cases whose phenomenon set is exactly `{AccelConcaveSpin, AccelSurfaceSpin}`: ```bash python scripts/filter_cases.py \ --split train \ --activity_type double \ --phenomena AccelConcaveSpin AccelSurfaceSpin \ --match_mode exact \ --output selected_cases.json ```

3.4 Randomly sample a fixed number of cases

`--num` is the global number of cases sampled after filtering (This is because the number of cases meeting the filtering criteria may be much larger than the number you need.). The default random seed is `42`. ```bash python scripts/filter_cases.py \ --split train \ --activity_type double \ --phenomena FrictionStop \ --num 3000 \ --seed 42 \ --output selected_cases.json ```

4. Download Selected Cases

Each selected case is downloaded as a zip file from the corresponding Hugging Face shard repository. ```bash python scripts/download.py \ --selection selected_cases.json \ --output_dir ./PhysInOne ``` If the dataset repositories are gated or private, pass a Hugging Face token: ```bash python scripts/download.py \ --selection selected_cases.json \ --output_dir ./PhysInOne \ --token YOUR_HF_TOKEN ``` By default, downloaded zip files are saved into a flat output folder. To preserve shard/split/activity structure: ```bash python scripts/download.py \ --selection selected_cases.json \ --output_dir ./PhysInOne \ --keep_shard_structure ``` The preserved structure is: ```text PhysInOne/ physinone_part1/ Train/ DoublePhysics/ AccelConcaveSpin_AccelSurfaceSpin__bg070__K5ER39_trajectory.zip ```

📦 Dataset Structure

```text AccelConcaveSpin__bg010__m3Zrtz_trajectory/ ├── AccelConcaveSpin__bg010__m3Zrtz_trajectory.json ├── blender_CineCamera_0.json ├── blender_CineCamera_1.json ├── blender_CineCamera_2.json ├── blender_CineCamera_3.json ├── blender_CineCamera_5.json ├── blender_CineCamera_6.json ├── blender_CineCamera_7.json ├── blender_CineCamera_8.json ├── blender_CineCamera_9.json ├── blender_CineCamera_10.json ├── blender_CineCamera_11.json ├── blender_CineCamera_12.json ├── blender_CineCamera_Moving.json ├── cameras.ply ├── caption.txt ├── points3d.ply ├── recorder_stats.json ├── static_camera_list.txt ├── CineCamera_0/ │ ├── depth/ (0000.npz ~ 0089.npz, 90 files) │ ├── rgb/ (0000.jpg ~ 0089.jpg, 90 files) │ └── seg/ (0000.npz ~ 0089.npz, 90 files) ├── CineCamera_1/ │ ... ├── CineCamera_2/ │ ... ├── CineCamera_3/ │ ... ├── CineCamera_5/ │ ... ├── CineCamera_6/ │ ... ├── CineCamera_7/ │ ... ├── CineCamera_8/ │ ... ├── CineCamera_9/ │ ... ├── CineCamera_10/ │ ... ├── CineCamera_11/ │ ... ├── CineCamera_12/ │ ... └── CineCamera_Moving/ ├── depth/ (0000.npz ~ 0089.npz, 90 files) ├── rgb/ (0000.jpg ~ 0089.jpg, 90 files) └── seg/ (0000.npz ~ 0089.npz, 90 files) ```

📝 Annotation Details

PhysInOne provides synchronized visual and physical annotations for each dynamic 3D scene.

•Depth

Depth maps are provided in `.npz` format and are expressed in meters.

•Segmentation

Segmentation masks encode background, static foreground objects, and dynamic foreground objects. Expected encoding: | Pixel Value | Meaning | | ----------- | -------------------------- | | `0` | Background | | `1-127` | Static foreground objects | | `128-255` | Dynamic foreground objects |

•Captions

Each scene includes a `caption.txt` file containing an English paragraph that describes the visual elements and the physical activity.

•Trajectories

Each sequence includes a JSON file with the same name as the sequence. This file records the per-frame poses of selected dynamic objects, including their rotations and translations in the world coordinate system.

JSON file structure

The JSON file contains two main parts: - `sequence_info`: basic information about the sequence, such as the total number of frames and the frame rate (`fps`). - `actors`: pose and metadata for dynamic objects, including object category, asset index path, actor type, and transformation data.

Actor-level pose storage

For each actor, the storage format depends on its `actor_type`: - If `actor_type` is `solid`, the object is treated as a single rigid body. Its per-frame pose is stored in the actor-level `transform_data` field, while the `components` field is empty. - If `actor_type` is `interactable`, the object is represented by multiple components. The actor-level `transform_data` field is empty, and the per-component poses are stored under `components[component_name].transform_data`.

Pose entry format in transform_data

Each entry in `transform_data` describes the pose of the object or component at a specific frame: - `frame`: frame index in the sequence - `time_seconds`: timestamp of the frame in seconds - `transform`: object or component transformation, including: - `location`: 3D position - `rotation`: rotation quaternion - `scale`: 3D scale

•Cameras

Each scene includes multiple camera viewpoints to support 3D perception, reconstruction, and physics-based visual reasoning tasks. - Taichi-based MPM simulations (elastic solids, plasticine, granular substances, some Newtonian and Non-Newtonian fluids): 15 static cameras + 1 dynamic camera - Other scenes: 12 static cameras + 1 dynamic camera Note: Camera IDs are not fixed across cases. The camera index mapping for each case is stored in `static_camera_list.txt` under that case directory.

Camera JSON structure

Per camera: - `frames`: list of per-frame 4×4 camera-to-world (C2W) transformation matrices in **Blender coordinate system** - `camera_angle_x`: horizontal field of view (FOV) in radians, can be used to compute intrinsic focal length - `img_w`, `img_h`: image width and height in pixels - `trajectory_name`: name of the camera trajectory - `total_frames`, `fps`: number of frames and frames per second

Dynamic camera behavior

- The dynamic camera moves along a path randomly sampled on a hemisphere surrounding the center of the main objects, providing diverse viewpoints. - JSON frame indices correspond directly to video frame indices.

•Point Clouds

Each scene should include `points.ply`. 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.

🧩 Data Fields

•Physical Phenomenon and Abbreviations

| ID | Physical Phenomenon | Abbreviation | Related Physical Laws | | ----- | --------------------------------------------------------- | -------------------- | --------------------- | | `1` | Object collide with static, stationary objects | MovingHitsFixed | Laws of Momentum | | `2` | Moving objects collide with non-static stationary objects | MovingHitsStationary | Laws of Momentum | | `3` | Two moving objects collide | MovingHitsMoving | Laws of Momentum | | `...` | ... | ... | ... |

Click to expand full abbreviation table

| ID | Physical Phenomenon | Abbreviation | Related Physical Laws | | ----- | ------------------------------------------------------------------------- | --------------------- | ------------------------------------------------------- | | `4` | Objects in equilibrium of wind and gravity | WindGravityBalance | Equilibrium, Aerodynamics, Gravity | | `5` | Wind applied to a stationary object | WindPushStationary | Aerodynamics | | `6` | Wind applied to objects moving in same direction | WindPushSameDir | Aerodynamics | | `7` | Wind applied to objects moving in the opposite direction | WindPushOppDir | Aerodynamics | | `8` | Wind applied to moving objects changes its velocity (applied at an angle) | WindDeflectMotion | Aerodynamics | | `9` | Object thrown up with angle | ObliqueProjectile | Gravity | | `10` | Objects falling straight down | VerticalFall | Gravity | | `11` | Objects rolling down a straight slope | RollDownSlope | Gravity, Friction | | `12` | Objects rolling up a slope | RollUpSlope | Gravity, Friction | | `13` | Magnetic Attraction | MagnetAttract | Magnetism | | `14` | Magnetic Repulsion | MagnetRepel | Magnetism | | `15` | Objects near uniformly rotating pillar | UniformPanelSpin | Laws of Rotation | | `16` | Objects near acceleratingly rotating pillar | AccelPanelSpin | Laws of Rotation | | `17` | Objects inside uniformly rotating bowl | UniformConcaveSpin | Equilibrium, Laws of Rotation, Gravity, Friction | | `18` | Objects inside acceleratingly rotating bowl | AccelConcaveSpin | Equilibrium, Laws of Rotation, Gravity, Friction | | `19` | Objects on uniformly rotating plane | UniformSurfaceSpin | Laws of Rotation, Friction | | `20` | Objects on acceleratingly rotating plane | AccelSurfaceSpin | Laws of Rotation, Friction | | `21` | Objects on coarse surface with friction | FrictionStop | Friction | | `22` | Spring is compressed | SpringCompress | Laws of Elasticity | | `23` | Spring is stretched | SpringStretch | Laws of Elasticity | | `24` | Breakable object shatters | ImpactFracture | Laws of Plasticity | | `25` | Mirror shatters | MirrorFragmentReflect | Laws of Plasticity, Law of Reflection | | `26` | Elastic rope connection | ElasticCouple | Laws of Elasticity | | `27` | Object bounces off spring board | SpringboardRebound | Laws of Elasticity, Laws of Momentum | | `28` | Objects interact with a balanced seesaw | SeesawCenterPivot | Laws of Torque | | `29` | Objects interact with an imbalanced seesaw | SeesawOffsetPivot | Laws of Torque | | `30` | Free balloon floats to ceiling | BalloonFloat | Laws of Buoyancy | | `31` | Tethered balloon pulls string taut | BalloonTether | Laws of Buoyancy, Rope Restraint | | `32` | Multiple balloons lifting | BalloonLift | Laws of Buoyancy, Rope Restraint, Gravity | | `33` | Laser hits flat mirror and reflects | FixedPlanarRedirect | Law of Reflection | | `34` | Laser reflects off multiple mirrors | FixedArrayRedirect | Law of Reflection | | `35` | Laser hits and reflects off concave mirror | FixedConcaveRedirect | Law of Reflection | | `36` | Laser hits and reflects off convex mirror | FixedConvexRedirect | Law of Reflection | | `37` | Mirror sweeps beam | DynMirrorRedirect | Law of Reflection | | `38` | Laser blocked by object | LaserBlock | Light Obstruction | | `39` | Mirror reflection | MirrorReflect | Law of Reflection | | `40` | Cart moving forward with rolling wheels | CartMove | Complex Mechanical Structure Constraints | | `41` | Objects on rotating turntable flies off | RotTurnableInertia | Laws of Rotation, Friction, Laws of Inertia | | `42` | Rotating block pushes another objects | RotBoardInertia | Laws of Inertia, Laws of Rotation, Laws of Momentum | | `43` | One object carrying another | LinCarryInertia | Laws of Inertia, Friction | | `44` | Catapult launches objects | CatapultLaunch | Special Mechanical Structure, Gravity | | `45` | Chain suspends objects | ChainSuspend | Complex Mechanical Structure Constraints, Gravity | | `46` | Objects Swing | SimplePendulum | Laws of Pendulum Motion, Gravity | | `47` | Double Pendulum Moves | DoublePendulum | Laws of Multiple Pendulum Motion, Gravity | | `48` | Crank push objects | CrankPush | Special Mechanical Structure | | `49` | Wall composed of square blocks collapses | BlockWallCollapse | Gravity, Structural Stability | | `50` | Wooden board supported by sticks collapses | StickSupportFail | Gravity, Structural Stability | | `51` | Objects float on the fluid surface | FloatOnLiquid | Laws of Buoyancy, Fluid Dynamics | | `52` | Objects drop into the fluid | DropInLiquid | Laws of Buoyancy, Fluid Dynamics | | `53` | Objects' movement causes fluid motion | MovingObjDriveLiquid | Fluid Dynamics | | `54` | Flowing fluid carries objects along | LiquidCarryMovingObj | Laws of Buoyancy, Fluid Dynamics | | `55` | Fluid flows against stationary objects | LiquidHitFixedObj | Fluid Dynamics | | `56` | Fluid transfers from one container to another | LiquidTransfer | Fluid Dynamics, Conservation of Mass, Surface Tension | | `57` | Fluid passes through several connected containers | LiquidMultiTransfers | Fluid Dynamics, Conservation of Mass, Surface Tension | | `58` | Fluid flows through grid-like structures | LiquidThroughGrid | Fluid Dynamics, Conservation of Mass | | `59` | Fluid moves across mountainous or uneven landscapes | LiquidAcrossUneven | Fluid Dynamics | | `60` | Increasing fluid volume elevates the surface level | LiquidRise | Fluid Dynamics | | `61` | Fluid flows along the contours of an object's surface | LiquidAlongContours | Fluid Dynamics | | `62` | Jet-like fluid projection upward or outward | JetLiquid | Fluid Dynamics | | `63` | Fluid exhibits surface tension | LiquidTension | Fluid Dynamics, Laws of Surface Tension | | `64` | Fluid refracts light when crossing media | LiquidRefraction | Fluid Dynamics, Optics, Law of Refraction (Snell's Law) | | `65` | Sticky fluid drips and accumulates on objects | StickyToObjects | Laws of Cohesion, Viscous Flow | | `66` | Sticky fluid falls from an object's surface | StickyFromObjects | Laws of Cohesion, Laws of Viscous Flow (Navier-Stokes) | | `67` | An elastic object falls and bounces on another surface | ElasticFall | Laws of Elasticity | | `68` | A plasticine object falls and deforms on a surface | PlasticineFall | Laws of Plasticity | | `69` | A Newtonian fluid falls and spreads across a surface | NewtonianFluidFall | Laws of Viscous Flow (Navier-Stokes) | | `70` | A Non-Newtonian fluid falls and flows with variable resistance | NonNewtonianFluidFall | Laws of Viscoplastics Flow | | `71` | A granular substance falls and disperses across a surface | GranularFall | Laws of Friction |

Example: MovingHitsStationary_WindDeflectMotion_BalloonFloat__bg140__TZlWl1 - The first three components correspond to specific physical phenomenon abbreviations (see table above). - `bg140` indicates that the scene uses background number 140. - The last six-character string (`TZlWl1`) is a unique hash code generated for this scene to guarantee uniqueness. This naming convention allows users to quickly parse scene metadata and link it to the corresponding physical phenomena, background, and unique identifier.

📜 License

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: - SketchFab: assets under various licenses, verified that AI-related usage is allowed. - Fab: assets under CC BY or Unreal Engine Standard License, explicitly permitting AI-related usage. - BlenderKit: distributed under Royalty-Free (RF) license. - ShareTextures: textures under CC0 license. 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.

📚 Citation

If you use PhysInOne in your research, please cite: ```bibtex @misc{zhou2026physinonevisualphysicslearning, title={PhysInOne: Visual Physics Learning and Reasoning in One Suite}, author={Siyuan Zhou and Hejun Wang and Hu Cheng and Jinxi Li and Dongsheng Wang and Junwei Jiang and Yixiao Jin and Jiayue Huang and Shiwei Mao and Shangjia Liu and Yafei Yang and Hongkang Song and Shenxing Wei and Zihui Zhang and Peng Huang and Shijie Liu and Zhengli Hao and Hao Li and Yitian Li and Wenqi Zhou and Zhihan Zhao and Zongqi He and Hongtao Wen and Shouwang Huang and Peng Yun and Bowen Cheng and Pok Kazaf Fu and Wai Kit Lai and Jiahao Chen and Kaiyuan Wang and Zhixuan Sun and Ziqi Li and Haochen Hu and Di Zhang and Chun Ho Yuen and Bing Wang and Zhihua Wang and Chuhang Zou and Bo Yang}, year={2026}, eprint={2604.09415}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2604.09415}, } ```

📮 Contact

For questions about the dataset, please contact: - {siyuan.zhou, hejun.wang, hu123.cheng, jinxi.li}@connect.polyu.hk, bo.yang@polyu.edu.hk