README.md

---
license: apache-2.0
task_categories:
  - visual-question-answering
tags:
  - autonomous-driving
  - vision-language
  - multimodal
  - benchmark
multimodal: true
pretty_name: ScenePilot-Bench
---


# **ScenePilot-Bench: A Large-Scale First-Person Dataset and Benchmark for Evaluation of Vision-Language Models in Autonomous Driving**

<div align="center">
  <img src="assets/The overall structure.png" width="800px">
  <p><em>Figure 1: Overview of the ScenePilot-Bench dataset and evaluation metrics.</em></p>
</div>

<p align="center">
  <a href="https://github.com/yjwangtj/ScenePilot-Bench">
    <img src="https://img.shields.io/badge/Project-Website-blue?style=flat-square">
  </a>
  <a href="https://huggingface.co/datasets/larswangtj/ScenePilot-4K/tree/main">
    <img src="https://img.shields.io/badge/Dataset-Download-green?style=flat-square">
  </a>
  <a href="https://arxiv.org/abs/2601.19582">
    <img src="https://img.shields.io/badge/Paper-Arxiv-red?style=flat-square">
  </a>
</p>

---

## 📦 Contents Overview

The dataset files in this repository can be grouped into the following categories.

---

## 1. Model Weight Files

- **ScenePilot_2.5_3b_200k_merged.zip**  
- **ScenePilot_2_2b_200k_merged.zip**

These two compressed files contain pretrained model weights obtained by training on a **200k-scale VQA training set** constructed in this work.

- The former corresponds to **Qwen2.5-VL-3B**
- The latter corresponds to **Qwen2-VL-2B**

Both models are trained using the same dataset and unified training pipeline, and are used in the main experiments and comparison studies.

---

## 2. Spatial Perception and Annotation Data

- **VGGT.zip**  
  Contains annotation data related to spatial perception tasks, including:
  - Ego-vehicle trajectory information  
  - Depth-related information  

  These annotations are used to support experiments involving trajectory prediction and spatial understanding.

- **YOLO.zip**  
  Provides 2D object detection results for major traffic participants.  
  All detections are generated by a unified detection model and are used as perception inputs for downstream VQA and risk assessment tasks.

- **scene_description.zip**  
  Contains scene description results generated from the original data, including:
  - Weather conditions  
  - Road types  
  - Other environmental and semantic attributes  

  These descriptions are used for scene understanding and for constructing balanced dataset splits.

---

## 3. Dataset Split Definition

- **split_train_test_val.zip**

This file contains the **original video-level dataset split**, including:
- Training set  
- Validation set  
- Test set  

All VQA datasets of different scales are constructed **strictly based on this video-level split** to avoid scene-level information leakage.

---

## 4. VQA Datasets

### 4.1 All-VQA

- **All-VQA.zip**

This archive contains all VQA data in JSON format.  
Files are organized according to training, validation, and test splits.

Examples include:
- `Deleted_2D_train_vqa_add_new.json`
- `Deleted_2D_train_vqa_new.json`

These files together form the complete training VQA dataset.  
Other files correspond to validation and test data.

---

### 4.2 Test-VQA

- **Test-VQA.zip**

This archive contains the **100k-scale VQA test datasets** used in the experiments.

- `Deleted_2D_test_selected_vqa_100k_final.json`  
  Used as the main test set in the primary experiments.

Additional test sets are provided for generalization studies:
- Files ending with `europe`, `japan-and-korea`, `us`, and `other` correspond to geographic generalization experiments.
- Files ending with `left` correspond to left-hand traffic country experiments.

Each test set contains **100k VQA samples**.

---

### 4.3 Train-VQA

- **Train-VQA.zip**

This archive contains training datasets of different scales:
- **200k VQA**
- **2000k VQA**

Additional subsets include:
- Files ending with `china`, used for geographic generalization experiments.
- Files ending with `right`, used for right-hand traffic country experiments.

---

## 5. Video Index and Download Information

- **video_name_all.xlsx**

This file lists all videos used in the dataset along with their corresponding download links.  
It is provided to support dataset reproduction and access to the original video resources.

---

## 🔧 Data Processing Utility

- **clip.py**

This repository provides a utility script for extracting image frames from raw videos.

The script performs the following operations:
- Trims a fixed duration from the beginning and end of each video  
- Samples frames at a fixed rate  
- Organizes extracted frames into structured folders  

---


## 📚Citation

```bibtex
@article@misc{wang2026scenepilotbenchlargescaledatasetbenchmark,
  title={ScenePilot-Bench: A Large-Scale Dataset and Benchmark for Evaluation of Vision-Language Models in Autonomous Driving}, 
  author={Yujin Wang and Yutong Zheng and Wenxian Fan and Tianyi Wang and Hongqing Chu and Daxin Tian and Bingzhao Gao and Jianqiang Wang and Hong Chen},
  year={2026},
  eprint={2601.19582},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2601.19582}, 
}
```

## License

[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.