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README.md
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---
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task_categories:
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- text-to-3d
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- image-to-3d
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- image-text-to-image
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- any-to-any
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tags:
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- Camera
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- 3D Vision
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- Spatial AI
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- Physical AI
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- World Model
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- Camera Parameter
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- APT-36K
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- Generation
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---
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# APT-36K-Camera
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Per-image camera parameter annotations for the **APT-36K** dataset
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(a large-scale animal pose estimation & tracking benchmark; 35,860 frames from 2,400 video clips across 30 species), 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.
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The collage above visualizes the camera maps on sample images — each
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pair shows the **up field** (green arrows: the projected gravity-up direction)
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and the **latitude field** (colored contours: angle above/below the horizon).
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## Format
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One `.tar` per shard (`apt36k_0000.tar` … ), each containing one `.json` per
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image whose name matches the source image stem (`<species>_<video>_frameN`).
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Each JSON holds the predicted monocular camera parameters:
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| Field | Meaning | Unit |
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|-------|---------|------|
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| `roll` | camera roll | radians |
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| `pitch` | camera pitch | radians |
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| `vfov` | vertical field-of-view | radians |
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| `k1` | radial distortion coefficient | – |
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| `parse_ok` | whether the model output parsed within valid ranges | bool |
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Example:
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```json
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{"roll": 0.0123, "pitch": -0.0871, "vfov": 0.4200, "k1": 0.0000, "parse_ok": true}
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```
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## Camera Parameter Distributions
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Histograms of the predicted roll / pitch / vertical-FoV over the whole dataset
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(proportion of valid samples per 10° bin; `parse_ok=False` excluded).
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| split | roll μ / med / σ | pitch μ / med / σ | FoV μ / med / σ |
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|-------|------------------|-------------------|-----------------|
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| all (35,661) | 0.2° / 0.0° / 3.5° | −4.9° / −3.7° / 11.3° | 24.1° / 20.3° / 6.0° |
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- **Roll** is tightly peaked at 0° (σ ≈ 3.5°; footage shot level).
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- **Pitch** is centered slightly negative (a mild downward-looking tendency).
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- **FoV** is narrow (median ≈ 20°, the tightest of our captioned sets) —
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consistent with telephoto wildlife videography that frames distant animals.
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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.
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### Dataset Download
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You can download the entire dataset using the following command:
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```bash
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hf download KangLiao/APT-36K-Camera --repo-type dataset
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```
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### Caption Pipeline
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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).
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### Citation
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If you find the captioned dataset useful for your research or applications, please cite our paper using the following BibTeX:
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```bibtex
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@article{liao2025puffin,
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title={Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation},
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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},
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journal={arXiv preprint arXiv:2510.08673},
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year={2025}
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}
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```
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