Datasets:

Chenwei1999
/

robointer-skill-annotations

license: cc-by-nc-sa-4.0
language:
  - en
task_categories:
  - robotics
  - video-classification
tags:
  - robotics
  - robot-manipulation
  - atomic-skills
  - skill-segmentation
  - video-understanding
  - robointer
  - automark
pretty_name: RoboInter Atomic-Skill Segment Annotations (AutoMark)
size_categories:
  - 100K<n<1M

RoboInter Atomic-Skill Segment Annotations (AutoMark)

Atomic-skill segment annotations only for robot-manipulation videos, curated by the AutoMark project. Each robot episode is segmented into atomic primitive-skill intervals (e.g. pick, place, pour) with second-aligned timestamps and verb(object)-style call targets, over the 15-label RoboInter primitive-skill taxonomy.

⚠️ This dataset contains annotations only — NO raw videos. The labels are derived from InternRobotics/RoboInter-Data, which is access-gated (you must accept its Community License + Privacy Policy) and licensed CC BY-NC-SA 4.0. To obtain the actual .mp4 videos referenced here, request access to RoboInter-Data directly and rebuild with the AutoMark export scripts. The file_name / video_path fields are RoboInter video identifiers, not redistributed media.

Scale


Episodes (primary/exterior camera)	235,880
Atomic-skill segment annotations	758,397
Skill taxonomy	15 labels (RoboInter primitive skills)
Source FPS	10.0 (dataset); timestamps in seconds

Skill taxonomy: transfer, pick, place, press, push, pull, twist, pour, fold, slide, insert, shake, strike, throw, manipulate

Files

annotation.json — the full folder-dataset annotation. Top-level metadata (skill_taxonomy, dataset_fps, counts) plus videos[]; each video has file_name, fps, source (droid/rh20t), source_member_path (path within the RoboInter release), and an annotations[] list of segments: {start, end, frame_start, frame_end, skill, call, text}. call is a verb(args)-style function string (args may be empty when the rule-based parser could not bind an object).
qwen/text.jsonl — 758,397 text-only evaluation rows for skill/call prediction (one segment per row): text (segment hint), gt_skill, target_call, allowed_skills, and a ready prompt.
qwen/visual_smoke_1024.jsonl — a 1,024-row visual smoke subset; same schema plus a relative video_path (video/<video_id>.mp4) for grounding against the (separately obtained) videos.
qwen/report.json — build report (row counts, taxonomy).

Filesystem paths have been relativized; no absolute paths are included.

Provenance & licensing

Curated by AutoMark (online atomic-skill induction): https://github.com/Chenwei-1999/AutoMark
Source: RoboInter-Data (InternRobotics/RoboInter-Data), itself built on DROID and RH20T — see each for their original licenses.
License: CC BY-NC-SA 4.0 (inherited from RoboInter). Non-commercial use only; derivatives must carry the same license; attribute RoboInter, DROID, and RH20T.

If you use these annotations, please cite RoboInter-Data and the upstream DROID / RH20T datasets.