| --- |
| task_categories: |
| - text-to-3d |
| - image-to-3d |
| - image-text-to-image |
| - any-to-any |
| tags: |
| - Camera |
| - 3D Vision |
| - Spatial AI |
| - Physical AI |
| - World Model |
| - Camera Parameter |
| - APTv2 |
| - Generation |
|
|
| --- |
| |
| # APTv2-Camera |
|
|
|  |
|
|
| Per-image camera parameter annotations for the **APTv2** dataset |
| (an animal pose estimation & tracking benchmark; 41,569 images across 9 shards), captioned by the [**Puffin-World**](https://github.com/KangLiao929/Puffin) model. More captioned datasets are provided in our [**Puffin-16M**](https://kangliao929.github.io/projects/puffin-16m/) website. |
|
|
| The collage above visualizes the camera maps on sample images — each |
| pair shows the **up field** (green arrows: the projected gravity-up direction) |
| and the **latitude field** (colored contours: angle above/below the horizon). |
|
|
| ## Format |
|
|
| One `.tar` per shard (`aptv2_0000.tar` … ), each containing one `.json` per |
| image whose name matches the source image stem. |
|
|
| Each JSON holds the predicted monocular camera parameters: |
|
|
| | Field | Meaning | Unit | |
| |-------|---------|------| |
| | `roll` | camera roll | radians | |
| | `pitch` | camera pitch | radians | |
| | `vfov` | vertical field-of-view | radians | |
| | `k1` | radial distortion coefficient | – | |
| | `parse_ok` | whether the model output parsed within valid ranges | bool | |
|
|
| Example: |
|
|
| ```json |
| {"roll": 0.0123, "pitch": -0.0871, "vfov": 0.4012, "k1": 0.0000, "parse_ok": true} |
| ``` |
|
|
| ## Camera Parameter Distributions |
|
|
| Histograms of the predicted roll / pitch / vertical-FoV over the whole dataset |
| (proportion of valid samples per 10° bin; `parse_ok=False` excluded). |
|
|
|  |
|
|
| | split | roll μ / med / σ | pitch μ / med / σ | FoV μ / med / σ | |
| |-------|------------------|-------------------|-----------------| |
| | all (41,349) | 0.2° / 0.0° / 3.5° | −5.1° / −3.7° / 11.2° | 24.2° / 22.9° / 6.0° | |
|
|
| - **Roll** is tightly peaked at 0° (σ ≈ 3.5°; footage shot level). |
| - **Pitch** is centered slightly negative (mild downward-looking tendency). |
| - **FoV** is notably narrow (median ≈ 23°, the tightest of our captioned sets) — |
| consistent with telephoto wildlife/animal photography that frames distant |
| subjects. |
|
|
| If you'd like a dataset with a more diverse and uniform distribution of camera parameters, please refer to our [Puffin-4M](https://huggingface.co/datasets/KangLiao/Puffin-4M) and [Puffin-16M](https://huggingface.co/datasets/KangLiao/Puffin-16M) datasets. |
|
|
| ### Dataset Download |
| You can download the entire dataset using the following command: |
| ```bash |
| hf download KangLiao/APTv2-Camera --repo-type dataset |
| ``` |
|
|
| ### Caption Pipeline |
| Beyond this captioned dataset, we also release **a complete captioning pipeline** for annotating camera parameters for arbitrary datasets, analyzing camera parameter distributions, and visualizing the corresponding camera maps. The pipeline is available in our [GitHub repository](https://github.com/KangLiao929/Puffin). |
|
|
|
|
| ### Citation |
| If you find the captioned dataset useful for your research or applications, please cite our paper using the following BibTeX: |
|
|
| ```bibtex |
| @article{liao2025puffin, |
| title={Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation}, |
| author={Liao, Kang and Wu, Size and Wu, Zhonghua and Jin, Linyi and Wang, Chao and Wang, Yikai and Wang, Fei and Li, Wei and Loy, Chen Change}, |
| journal={arXiv preprint arXiv:2510.08673}, |
| year={2025} |
| } |
| ``` |
|
|
