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
- EgoObjects
- Generation
EgoObjects-Camera
Per-image camera parameter annotations for the EgoObjects dataset (a large-scale egocentric object dataset from Meta AI; 241,658 images across 49 shards), 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 shard (egoobjects_part1_*.tar, egoobjects_part2_*.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": -0.4271, "vfov": 1.0123, "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 (241,554) | −0.1° / 0.0° / 8.0° | −24.5° / −25.6° / 15.3° | 39.3° / 36.7° / 10.2° |
- Roll is centered at 0° with a moderate spread (σ ≈ 8°; some head tilt).
- Pitch is strongly negative (median ≈ −26°) — a hallmark of egocentric, head-mounted capture, where the camera consistently looks down at objects, hands and tabletops.
- FoV concentrates in 30–45° (median ≈ 37°).
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/EgoObjects-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}
}