| --- |
| license: cc-by-4.0 |
| task_categories: |
| - video-classification |
| - visual-question-answering |
| - text-generation |
| language: |
| - en |
| tags: |
| - egocentric |
| - ego4d |
| - first-person-video |
| - activity-recognition |
| - narrations |
| - temporal-localization |
| - hands-and-objects |
| size_categories: |
| - n<1K |
| pretty_name: Egocentric Activity Sample Dataset |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: "data/train-*.parquet" |
| --- |
| |
| # Egocentric Activity Sample Dataset |
|
|
| A small-scale egocentric (first-person) video dataset with **Ego4D-style annotations**, designed for quick prototyping and experimentation with egocentric video understanding tasks. |
|
|
| ## Dataset Summary |
|
|
| | Metric | Value | |
| |--------|-------| |
| | **Video clips** | 19 | |
| | **Total duration** | ~9.5 minutes | |
| | **Resolution** | 960x540 (540p) | |
| | **FPS** | 30 | |
| | **Narrations** | 99 | |
| | **NLQ queries** | 57 | |
| | **Moment annotations** | 19 | |
| | **FHO actions** | 57 | |
| | **Total size** | ~54 MB | |
|
|
| ## Activities Covered |
|
|
| | Scenario | Activities | Clips | |
| |----------|-----------|-------| |
| | **Object Manipulation** | Pick & place, reorient & place, bimanual manipulation | 10 | |
| | **Cleaning** | Organizing bathroom, tidying bedroom | 6 | |
| | **Cooking** | Washing dishes at the sink | 3 | |
|
|
| ## Dataset Structure |
|
|
| ``` |
| ├── videos/ # 19 egocentric video clips (30s each, 540p, h264) |
| │ ├── ego_pick_place_01.mp4 |
| │ ├── ego_washing_dishes_01.mp4 |
| │ └── ... |
| ├── annotations/ |
| │ ├── metadata.json # Video metadata (UIDs, duration, resolution, scenarios) |
| │ ├── narrations.json # Dense temporal narrations (Ego4D narration format) |
| │ ├── nlq.json # Natural Language Queries (Ego4D NLQ format) |
| │ ├── moments.json # Temporal activity moments (Ego4D moments format) |
| │ ├── fho_actions.json # Forecasting Hands & Objects actions (Ego4D FHO format) |
| │ └── taxonomy.json # Activity/verb/noun taxonomy |
| └── metadata.csv # Flat CSV for HuggingFace datasets library |
| ``` |
|
|
| ## Annotation Formats |
|
|
| All annotations follow the [Ego4D v2 annotation schema](https://ego4d-data.org/docs/data/annotations-schemas/). |
|
|
| ### Narrations |
| Dense temporal narrations using `#C` (camera wearer) and `#O` (other person) tags: |
| ```json |
| { |
| "timestamp_sec": 8.0, |
| "narration_text": "#C C applies soap to the sponge", |
| "is_camera_wearer": true |
| } |
| ``` |
|
|
| ### Natural Language Queries (NLQ) |
| Temporal grounding queries with response windows: |
| ```json |
| { |
| "query": "What dish did I wash?", |
| "clip_start_sec": 1.0, |
| "clip_end_sec": 24.0 |
| } |
| ``` |
|
|
| ### Moments |
| Temporal activity localization labels: |
| ```json |
| { |
| "label": "wash_dishes_/_utensils_/_bakeware_etc.", |
| "start_time": 1.0, |
| "end_time": 28.0 |
| } |
| ``` |
|
|
| ### FHO Actions |
| Hands & objects interaction annotations with critical frames: |
| ```json |
| { |
| "structured_verb": "scrub", |
| "structured_noun": "dish", |
| "critical_frames": { |
| "pre_frame": {"sec": 11.5}, |
| "contact_frame": {"sec": 13.0}, |
| "pnr_frame": {"sec": 12.7}, |
| "post_frame": {"sec": 14.5} |
| } |
| } |
| ``` |
|
|
| ## Usage |
|
|
| ### With HuggingFace Datasets |
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("WhissleAI/egocentric-activity-sample") |
| ``` |
|
|
| ### Direct JSON Loading |
| ```python |
| import json |
| with open("annotations/narrations.json") as f: |
| narrations = json.load(f) |
| for video in narrations["videos"]: |
| for n in video["narrations"]: |
| print(f"[{n['timestamp_sec']:.1f}s] {n['narration_text']}") |
| ``` |
|
|
| ## Sources |
|
|
| Video clips are derived from publicly available egocentric video datasets: |
| - [HoyerChou/EgocentricVideos](https://huggingface.co/datasets/HoyerChou/EgocentricVideos) — pick-place, reorient, bimanual manipulation |
| - [TrainThemAI/POV-Egocentric-Video-Robotics-FHD-Samples](https://huggingface.co/datasets/TrainThemAI/POV-Egocentric-Video-Robotics-FHD-Samples) — household activities |
|
|
| All videos downscaled to 540p and trimmed to 30-second clips. |
|
|
| ## License |
|
|
| CC-BY-4.0 — see source datasets for their respective licenses. |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite the original Ego4D paper for the annotation format: |
|
|
| ```bibtex |
| @inproceedings{grauman2022ego4d, |
| title={Ego4d: Around the world in 3,000 hours of egocentric video}, |
| author={Grauman, Kristen and others}, |
| booktitle={CVPR}, |
| year={2022} |
| } |
| ``` |
|
|
