--- 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 - DeepFashion - Generation --- # DeepFashion-Camera ![camera map collage](analysis/DeepFashion-Camera.png) Per-image camera parameter annotations for the **DeepFashion** dataset (full-body fashion model photographs; 13,679 images), 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 (`deepfashion_0000.tar` … ), each containing one `.json` per image whose name matches the source image stem. Only the main person photograph (the `image` field) is captioned; auxiliary pose / cloth views are excluded. 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": 0.0087, "vfov": 0.5691, "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). ![deepfashion camera stats](analysis/deepfashion_camera_stats.png) | split | roll μ / med / σ | pitch μ / med / σ | FoV μ / med / σ | |-------|------------------|-------------------|-----------------| | all (13,675) | 0.1° / 0.3° / 3.5° | 1.1° / 0.4° / 3.6° | 32.6° / 32.1° / 3.4° | - **Roll** and **pitch** are both tightly centered near 0° (level, front-on full-body shots). - **FoV** is remarkably consistent (σ ≈ 3.4°, the tightest of our captioned sets) — studio fashion photography frames the model with a near-constant focal length. 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/DeepFashion-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} } ```