Robotics Video Question Answering Dataset

RoboVQA contains video and text data for training models to answer questions about robotic scenes. The dataset includes over 100,000 entries, as indicated by its Hugging Face size category. It was created by Tianli and last updated in July 2025.

Use Cases

• Train models to answer textual questions about actions and objects in robotic video scenes.
• Benchmark the performance of multimodal systems on video-based question answering tasks.
• Generate descriptive captions or instructions from video frames using paired text annotations.

Strengths

• Dataset size exceeds 100,000 entries.
• Combines video modality with text annotations for multimodal tasks.

Limitations

• Specific row count, column details, and video resolution are unknown.
• Geographic and temporal coverage of the robotic scenes is unspecified.

Provenance

Source

Hugging Face platform.

Freshness

Last updated in July 2025.