|
--- |
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dataset_info: |
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- config_name: tqa |
|
features: |
|
- name: id |
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dtype: string |
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- name: text |
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dtype: string |
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- name: oracle_answer |
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dtype: string |
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- name: oracle_option |
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dtype: string |
|
- name: oracle_full_answer |
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dtype: string |
|
splits: |
|
- name: test |
|
num_bytes: 4723238 |
|
num_examples: 4635 |
|
download_size: 804261 |
|
dataset_size: 4723238 |
|
- config_name: vqa |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: text |
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dtype: string |
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- name: image |
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dtype: image |
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- name: oracle_answer |
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dtype: string |
|
- name: oracle_option |
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dtype: string |
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- name: oracle_full_answer |
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dtype: string |
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splits: |
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- name: test |
|
num_bytes: 733091578.0 |
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num_examples: 4635 |
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download_size: 712137895 |
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dataset_size: 733091578.0 |
|
- config_name: vtqa |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: image |
|
dtype: image |
|
- name: oracle_answer |
|
dtype: string |
|
- name: oracle_option |
|
dtype: string |
|
- name: oracle_full_answer |
|
dtype: string |
|
splits: |
|
- name: test |
|
num_bytes: 736109315.0 |
|
num_examples: 4635 |
|
download_size: 712879771 |
|
dataset_size: 736109315.0 |
|
configs: |
|
- config_name: tqa |
|
data_files: |
|
- split: test |
|
path: tqa/test-* |
|
- config_name: vqa |
|
data_files: |
|
- split: test |
|
path: vqa/test-* |
|
- config_name: vtqa |
|
data_files: |
|
- split: test |
|
path: vtqa/test-* |
|
--- |
|
|
|
## 🤔 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 |
|
1. **Spatial-Map**: Understanding spatial relationships between objects in map-based scenarios |
|
2. **Maze-Nav**: Testing navigation through complex environments |
|
3. **Spatial-Grid**: Evaluating spatial reasoning within structured environments |
|
4. **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](https://huggingface.co/docs/datasets/en/quickstart): |
|
|
|
```python |
|
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 |
|
|
