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license: mit
library_name: peft
pipeline_tag: image-text-to-text
---
# D2-V2X: Depth-Driven Cooperative V2X Reasoning for Autonomous Driving
This repository contains the model weights (adapter) for **D2-V2X**, a spatially-aware Question-Rationale-Answer (QRA) framework designed for cooperative autonomous driving.
[**Paper (arXiv)**](https://arxiv.org/abs/2605.24098) | [**GitHub**](https://github.com/KevinRichard1/D2-V2X) | [**Dataset**](https://huggingface.co/datasets/kr301/d2v2x-qra)
## Overview
D2-V2X addresses sensor occlusions in single-vehicle Vision-Language Models (VLMs) by establishing a benchmark for cooperative reasoning using multimodal vehicle and infrastructure sensors (V2X). It establishes a baseline that aligns 3D LiDAR features with the VLM's latent space, enforcing Chain-of-Thought (CoT) rationales to articulate spatial relations explicitly.
## Usage
For environment setup and data preparation, please refer to the [official GitHub repository](https://github.com/KevinRichard1/D2-V2X).
### Training
To train the model using the provided pipeline:
```bash
python train.py \
--qwen_path="/path/to/qwen/model" \
--train_path="/path/to/train/dataset" \
--val_path="/path/to/val/dataset" \
--img_path="/path/to/images" \
--train_feature_path="/path/to/train/lidar/features" \
--val_feature_path="/path/to/val/lidar/features" \
--output_path="/checkpoint/path" \
--mode="" \
--stage="" \
--lr=2e-5 \
--epochs=3 \
--batch_size=1 \
--accum_steps=64
```
### Evaluation
To evaluate the model:
```bash
python evaluate.py \
--qwen_path="/path/to/qwen/model" \
--checkpoint_path="/checkpoint/path" \
--inference \
--evaluate \
--mode="" \
--json_path="/path/to/test/dataset" \
--img_path="/path/to/images" \
--test_feature_path="/path/to/test/lidar/features" \
--inference_save_path="results.json"
```
## Citation
If you find this work useful, please cite:
```bibtex
@misc{richard2026d2v2xdepthdrivencooperativev2x,
title={D2-V2X: Depth-Driven Cooperative V2X Reasoning for Autonomous Driving},
author={Kevin Richard and Alphin Varghese and Colin Pham and David Oh and Srijan Das},
year={2026},
eprint={2605.24098},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2605.24098},
}
``` |