---
language:
- en
license: apache-2.0
---
# 360°-Motion Dataset

[Project page](http://fuxiao0719.github.io/projects/3dtrajmaster) | [Paper](https://drive.google.com/file/d/111Z5CMJZupkmg-xWpV4Tl4Nb7SRFcoWx/view) | [Code](https://github.com/kwaiVGI/3DTrajMaster)

### Acknowledgments
We thank Jinwen Cao, Yisong Guo, Haowen Ji, Jichao Wang, and Yi Wang from Kuaishou Technology for their help in constructing our 360°-Motion Dataset.

![image/png](imgs/dataset.png)

### News
- [2024-12] We release the V1 dataset (72,000 videos consists of 50 entities, 6 UE scenes, and 121 trajectory templates).
  
### Data structure

 ```
  ├── 360Motion-Dataset                      Video Number        Cam-Obj Distance (m)
    ├── 480_720/384_672
        ├── Desert (desert)                    18,000               [3.06, 13.39]
            ├── location_data.json
        ├── HDRI                                                      
            ├── loc1 (snowy street)             3,600               [3.43, 13.02]
            ├── loc2 (park)                     3,600               [4.16, 12.22]
            ├── loc3 (indoor open space)        3,600               [3.62, 12.79]
            ├── loc11 (gymnastics room)         3,600               [4.06, 12.32]
            ├── loc13 (autumn forest)           3,600               [4.49  11.91]
            ├── location_data.json
        ├── RefPic
        ├── CharacterInfo.json
        ├── Hemi12_transforms.json
  ```

**(1) Released Dataset Information**

| Argument                | Description |Argument                | Description |
|-------------------------|-------------|-------------------------|-------------|
| **Video Resolution**    | (1) 480×720 (2) 384×672    |       **Frames/Duration/FPS**        | 99/3.3s/30  |
| **UE Scenes**    | 6 (1 desert+5 HDRIs)  |       **Video Samples**        | (1) 36,000 (2) 36,000 |
| **Hemi12_transforms.json**    | 12 surrounding cameras |      **CharacterInfo.json**        | entity prompts  |
| **RefPic**    | 50 animals     |       **1/2/3 Trajectory Templates**       | 36/60/35 (121 in total) |
| **{D/N}_{locX}** | {Day/Night}_{LocationX} |  **{C}_ {XX}_{35mm}** | {Close-Up Shot}_{Cam. Index(1-12)} _{Focal Length}|

**(2) Difference with the Dataset to Train on Our Internal Video Diffusion Model**

The release of the full dataset regarding more entities and UE scenes is 1) still under our internal license check, 2) awaiting the paper decision.

|  Argument              | Released Dataset |       Our Internal Dataset|
|-------------------------|-------------|-------------------------|
| **Video Resolution**    | (1) 480×720 (2) 384×672 |       384×672     |
| **Entities**    | 50 (all animals)     |      70 (20 humans+50 animals)  |
| **Video Samples**    | (1) 36,000 (2) 36,000   |    54,000   |
| **Scenes**    | 6  |   9 (+city, forest, asian town)  |
| **Trajectory Templates**    | 121 |   96  |

**(3) Load Dataset Sample**

1. Change root path to `dataset`. We provide a script to load our dataset (video & entity & pose sequence) as follows. It will generate the sampled video for visualization in the same folder path.

    ```bash
    python load_dataset.py
    ```

2. Visualize the 6DoF pose sequence via Open3D as follows.

    ```bash
    python vis_trajecotry.py
    ```
    After running the visualization script, you will get an interactive window like this.

    <img src="imgs/vis_objstraj.png" width="350" />