Zoo-Bus VQA: Synthetic Visual Question Answering for Spatial Reasoning

Zoo-Bus VQA is a synthetic visual question answering dataset built for spatial reasoning and object-centric grounding. It contains generated scenes with benches, stop signs, people, animals, and a clock object representing a bus. The dataset was created by author aprilavrilivan and last updated on March 22, 2026.

Use Cases

• Fine-tuning vision-language models for spatial reasoning based on generated scenes with objects and directional cues.
• Evaluating object-centric grounding capabilities based on the presence of animals, people, and stop signs.
• Benchmarking counting and structured visual reasoning tasks as mentioned in the dataset description.

Strengths

• Dataset is explicitly designed for spatial reasoning and object-centric grounding tasks.
• Scenes contain specific, structured elements like a clock object and a red heading dot for directional context.
• Last updated on March 22, 2026, indicating recent maintenance.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and dataset size are unknown, which may limit suitability assessment.
• Data is synthetic, which may not fully capture the complexity of real-world visual scenes.

Provenance

Source

huggingface

Collection Method

Synthetically generated.

Freshness

Last updated 2026-03-22 08:30:54