Datasets:

KangLiao
/

GPIC-Camera

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
  - GPIC
  - Generation

GPIC-Camera

Per-image camera parameter annotations for the GPIC dataset (train / test / val; train = 8,000 shards, test = 1,000,000 images, val = 200,000 images), captioned by the Puffin-World model. More captioned datasets are provided in our 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 source shard, under train/, test/, val/ (gpic_train_00000.tar … , gpic_test_00000.tar … , gpic_val_00000.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:

{"roll": 0.0123, "pitch": -0.0871, "vfov": 1.0123, "k1": 0.0000, "parse_ok": true}

Camera Parameter Distributions

Histograms of the predicted roll / pitch / vertical-FoV (proportion of valid samples per 10° bin; parse_ok=False excluded; computed on a ~4.9M-image sample across train/test/val).

split	roll μ / med / σ	pitch μ / med / σ	FoV μ / med / σ
sample (4.9M)	0.1° / 0.0° / 5.6°	−2.6° / −1.3° / 13.0°	33.8° / 31.2° / 11.6°

Roll is sharply peaked at 0° (images shot upright/level).
Pitch is centered slightly negative (mild downward-looking tendency).
FoV concentrates in 20–45° (median ≈ 31°) with a long wide-angle tail.

If you'd like a dataset with a more diverse and uniform distribution of camera parameters, please refer to our Puffin-4M and Puffin-16M datasets.

Dataset Download

You can download the entire dataset using the following command:

hf download KangLiao/GPIC-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.

Citation

If you find the captioned dataset useful for your research or applications, please cite our paper using the following 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}
  }