pretty_name: WGO-Bench
task_categories:
- robotics
- video-classification
language:
- en
tags:
- temporal-segmentation
- subtask-annotation
- robotics
- robot-learning
- benchmark
license: cc-by-nc-sa-4.0
WGO-Bench
MacroData's WGO-Bench is a benchmark for evaluating timestamped subtask annotations from robot and egocentric manipulation videos. MacroData describes the benchmark and its annotation approach in Segmenting Robot Video into Actionable Subtasks.
The upstream repository's summary.json states that its timeline reannotations were applied only to the 25 homer_* episodes, while the DROID and Galaxea rows were left unchanged. During our review of all 100 episodes, we found additional annotation issues. We discuss those issues and our reannotation process in the VideoDB WGO-Bench reannotation report.
This dataset retains the original videos and perception data and replaces the task and timestamped subtask annotations with our reviewed annotations.
Dataset
- Episodes: 100
- Corrected subtask segments: 534
- Families: 50 DROID, 25 Galaxea, and 25 HOMER
- Format: Parquet
- Videos: MP4 bytes embedded in each row
Each row contains the episode ID, video, high-level instruction, timestamped subtask segments, metadata, and available perception state.
License
The source dataset is licensed CC BY-NC-SA 4.0. This dataset uses the same license.