| --- |
| license: other |
| license_name: bop-motion-mcq-mixed-provenance |
| license_link: LICENSE.md |
| task_categories: |
| - visual-question-answering |
| - video-classification |
| language: |
| - en |
| tags: |
| - video |
| - motion |
| - 6dof |
| - temporal-reasoning |
| - multiple-choice |
| - object-motion |
| pretty_name: BOP-Motion-MCQ (6-DoF motion questions) |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: val |
| path: val/metadata.parquet |
| --- |
| |
| # BOP-Motion-MCQ — multiple-choice motion questions over dense 6-DoF video |
|
|
| **Multiple-choice questions about how objects move**, derived exactly from **dense |
| 6-DoF (object→camera) pose trajectories** rather than guessed from pixels. Each row pairs |
| a short 6fps video clip with one motion MCQ, its per-second motion trajectory, and the |
| whole-video aggregated answer. The intended task: watch the clip and pick the motion that |
| actually happens. |
|
|
| Built with the [`motion-qa`](https://github.com/dherrero12/motion-qa) pipeline |
| (`motion_qa.datagen.bop_mcq_questions`). |
|
|
| ## The four question types |
|
|
| | `qa_type` | answer space | derived from | |
| |---|---|---| |
| | `motion_direction` | left / right · up / down · toward / away | Δtranslation of one object | |
| | `rotation_spin` | clockwise / counter-clockwise | angular-velocity axis vs. the camera | |
| | `speed` | faster / slower · speeding up / slowing down | \|velocity\| and its trend | |
| | `relative_motion` | approaching / receding | two objects (or object vs. camera) | |
|
|
| Every question always includes an explicit **"no consistent ⟨motion⟩"** option. |
|
|
| ## How the answer is derived (two-step, noise-guarded) |
|
|
| 1. **Per-second trajectory.** The 6-DoF track is resampled to **6 fps**, swept with |
| sliding 1-second windows (step 1 frame), and each window yields an instantaneous |
| motion signal (direction axis / spin sign / speed / inter-object distance). Windows |
| below an **adaptive noise floor** (a fraction of a high percentile of the track's own |
| magnitude distribution — not a hand-tuned threshold) are marked inactive. Windows are |
| binned into 1-second labels: the `per_second` list **is** the motion story. |
| 2. **Whole-video answer with an anti-overfit guard.** The per-second labels are |
| aggregated, but the answer is only *solidified* (`decided = true`) when **both** gates |
| pass: the dominant label is supported by at least `min_observations` active bins |
| (default 2) **and** accounts for more than `dominance_threshold` (default 80%) of the |
| active bins. Otherwise the answer is the explicit **"no consistent …"** option |
| (`decided = false`). The `aggregation` struct records `dominant`, `dominant_frac`, |
| `n_active`, `n_supporting`, and both gate settings. |
|
|
| ## The three sources (all 6-DoF pose GT) |
|
|
| | `source` | motion | timing | notes | |
| |---|---|---|---| |
| | `ycbineoat` | **object moves**, camera static | real seconds (~30fps → 6fps) | single YCB object per sequence — so **no `relative_motion`** here | |
| | `hope_video` | **camera moves** over a static multi-object tabletop | frame-index / estimated `fps_native` | multi-object; motion is camera-perspective parallax | |
| | `bop_ycbv` | **camera moves**, objects static | **sparse, irregular BOP19 keyframes** | timing is **ordinal / approximate**; windows with undefined or too-large Δt are skipped — the row/evidence flags this honestly | |
|
|
| Per-source caveats to keep in mind: |
|
|
| - **`ycbineoat`** is the only source where motion is literally the object's own |
| translation/rotation; the other two are camera-perspective. |
| - **`bop_ycbv`** frames are irregular keyframes (im_id gaps up to ~900). `t` is not a |
| uniform timeline — spacing is ordinal and timing is approximate; do not read the |
| per-second bins as exact wall-clock seconds for this source. |
| - **BOP-HOPE is excluded**: its BOP test split ships **no pose ground truth**, so no |
| motion can be derived. (The `hope_video` source above is the *HOPE-Video* release, |
| which does carry per-frame camera + object poses.) |
| |
| ## What's in the repo |
| |
| ``` |
| val/metadata.parquet / .jsonl # the table (load_dataset); per_second + aggregation inline |
| val/metadata.csv # browsable view (heavy per_second/evidence dropped) |
| frames/<source>__<seq>.zip # the 6fps JPEG frames (rgb/000000.jpg …), one zip per sequence |
| # (+ mask/000000.png where the source ships per-object masks) |
| README.md # this card |
| LICENSE.md # full license + attribution (mixed-provenance) |
| ``` |
| |
| Only sequences that have shipped rows are included, and the frames are **re-encoded to |
| JPEG and downscaled** (longest side ≤ 640 px) — the lossless PNG sources are ~100 MB per |
| sequence and the model only needs to watch the 6fps video. |
| |
| ## Row schema (`val/metadata.parquet` / `.jsonl`) |
| |
| One row per Item (one MCQ over one or two tracked objects): |
| |
| | field | type | meaning | |
| |---|---|---| |
| | `id` | string | `⟨source⟩/⟨seq⟩/⟨qa_type⟩/⟨obj⟩` (+ `/vs⟨obj2⟩` for relative), unique | |
| | `source` | string | `ycbineoat` \| `hope_video` \| `bop_ycbv` | |
| | `seq_key` | string | e.g. `bop_ycbv/000048` | |
| | `qa_type` | string | `motion_direction` \| `rotation_spin` \| `speed` \| `relative_motion` | |
| | `reference_frame` | string | `camera` \| `object_local` \| `relative` | |
| | `object_ids` | list[int] | the tracked object slot(s) | |
| | `category` | string | object name(s), e.g. `master chef can` | |
| | `question` / `options` / `answer_idx` / `answer_text` | string / list / int / string | the MCQ (answer = the aggregated whole-video decision) | |
| | `per_second` | string (JSON) | list of `{second,t0,t1,label,active,magnitude,evidence}` — the trajectory | |
| | `aggregation` | string (JSON) | `{dominant,dominant_frac,n_active,n_supporting,min_observations,dominance_threshold,decided}` | |
| | `n_frames` / `fps` | int / float | resampled clip geometry (`fps` = 6) | |
| | `frames_zip` | string | path to this sequence's frame zip in the repo | |
| | `corrected` | bool | the auto-derived answer was fixed by a human reviewer | |
| | `verified` | bool | human-verified (the publish gate) | |
| | `note` | string | reviewer note, if any | |
| | `evidence` | string (JSON) | provenance for the derivation (`qa_type`, `timing`, gate stats, trajectory, …) | |
| |
| `per_second`, `aggregation`, and `evidence` are **JSON-encoded strings** so their nested, |
| per-`qa_type`-varying payloads survive parquet's columnar schema — `json.loads` to expand |
| them. The CSV view drops `per_second` and `evidence` for browsability. |
| |
| ## Quickstart — `load_dataset` |
| |
| ```python |
| import json |
| from datasets import load_dataset |
| |
| ds = load_dataset("livctr/bop-motion-mcq", split="val") |
| row = ds[0] |
| print(row["question"]) |
| print(row["options"][row["answer_idx"]]) |
| |
| trajectory = json.loads(row["per_second"]) # per-second motion labels |
| agg = json.loads(row["aggregation"]) # decided? dominant? gate stats |
| # frames come from frames/<seq_key with '/'→'__'>.zip (JPEGs rgb/000000.jpg …) |
| ``` |
| |
| ## License & attribution |
| |
| BOP-Motion-MCQ is **non-commercial, research-only**, and **mixed-provenance**. The |
| questions/trajectories/metadata added here are the new material; each source keeps its |
| origin license (YCBInEOAT, HOPE-Video, and YCB-Video/BOP). Per-source terms are in |
| [`LICENSE.md`](LICENSE.md); use of a source's frames is governed by that source's license. |
| Any use must cite the underlying datasets (see `LICENSE.md`). |
| |
