Egocentric Affordance Dataset
First-person affordance labels for manipulation
A CC-BY-4.0 egocentric image dataset with affordance, task, and view labels for robotics and embodied-AI perception tasks.
Affordance pretraining
Useful for dataset curation labels even when source videos are not robot trajectories.
Inspect schema and run a bounded sample audit before committing to the full release.
Has observation, action/state proxy, and task or language context.
fit 85 · confidence 55
Has rich observation and semantic context, but limited geometry/sim-real alignment.
fit 68 · confidence 55
Contains observation, intent, action/state, and feedback-like supervision.
fit 88 · confidence 55
Verified facts and provenance
Claims, metadata verification, and sample verification are shown separately.
Unknown — no machine-readable schema facts have been captured.
Unknown — metadata conclusions do not prove sample coverage, alignment, or file integrity.
Declared loop signal coverage
Signals inferred from official metadata; Data pipeline verification is still pending.
Observation / ego video
images · image paths · Useful for dataset curation labels even when source videos are not robot trajectories. · A CC-BY-4.0 egocentric image dataset with affordance, task, and view labels for robotics and embodied-AI perception tasks.
Action / hand pose / robot state
Object interaction mining · Manipulation-relevant frame filtering · First-person affordance labels for manipulation
Gaze / attention
No decision-grade evidence captured yet.
Language intent / task phase
affordance label · task label · view label · Useful for dataset curation labels even when source videos are not robot trajectories.
Feedback / correction / failure
affordance label · Affordance pretraining · First-person affordance labels for manipulation · A CC-BY-4.0 egocentric image dataset with affordance, task, and view labels for robotics and embodied-AI perception tasks.
Sim-real pairing
No decision-grade evidence captured yet.
License / format / access
Open · CC-BY-NC · image paths · metadata tables
Model and task fit · OpenBot inference
Has observation, action/state proxy, and task or language context.
fit 85 · confidence 55
Has rich observation and semantic context, but limited geometry/sim-real alignment.
fit 68 · confidence 55
Contains observation, intent, action/state, and feedback-like supervision.
fit 88 · confidence 55
Has failure/evaluation-style labels with action or manipulation context.
fit 82 · confidence 55
Good tasks
Blockers and unresolved evidence
- Gaze / attentionunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
- Sim-real pairingunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
Raw dataset signals
OpenBot fit
- Affordance pretraining
- Object interaction mining
- Manipulation-relevant frame filtering
Integration notes
- Useful for dataset curation labels even when source videos are not robot trajectories.
- Open license requires attribution.