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🤔 About SpatialEval
SpatialEval is a comprehensive benchmark for evaluating spatial intelligence in LLMs and VLMs across four key dimensions:
- Spatial relationships
- Positional understanding
- Object counting
- Navigation
Benchmark Tasks
- Spatial-Map: Understanding spatial relationships between objects in map-based scenarios
- Maze-Nav: Testing navigation through complex environments
- Spatial-Grid: Evaluating spatial reasoning within structured environments
- Spatial-Real: Assessing real-world spatial understanding
Each task supports three input modalities:
- Text-only (TQA)
- Vision-only (VQA)
- Vision-Text (VTQA)
📌 Quick Links
Project Page: https://spatialeval.github.io/
Paper: https://arxiv.org/pdf/2406.14852
Code: https://github.com/jiayuww/SpatialEval
Talk: https://neurips.cc/virtual/2024/poster/94371
🚀 Quick Start
📍 Load Dataset
SpatialEval provides three input modalities—TQA (Text-only), VQA (Vision-only), and VTQA (Vision-text)—across four tasks: Spatial-Map, Maze-Nav, Spatial-Grid, and Spatial-Real. Each modality and task is easily accessible via Hugging Face. Ensure you have installed the packages:
from datasets import load_dataset
tqa = load_dataset("MilaWang/SpatialEval", "tqa", split="test")
vqa = load_dataset("MilaWang/SpatialEval", "vqa", split="test")
vtqa = load_dataset("MilaWang/SpatialEval", "vtqa", split="test")
⭐ Citation
If you find our work helpful, please consider citing our paper 😊
@inproceedings{wang2024spatial,
title={Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models},
author={Wang, Jiayu and Ming, Yifei and Shi, Zhenmei and Vineet, Vibhav and Wang, Xin and Li, Yixuan and Joshi, Neel},
booktitle={The Thirty-Eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}
💬 Questions
Have questions? We're here to help!
- Open an issue in the github repository
- Contact us through the channels listed on our project page