Add RoboInter atomic-skill segment annotations (annotations only; CC BY-NC-SA 4.0; derived from InternRobotics/RoboInter-Data)
d70dbdf verified | 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**](https://github.com/Chenwei-1999/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`](https://huggingface.co/datasets/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](https://droid-dataset.github.io/) and [RH20T](https://rh20t.github.io/) — 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. | |