V2V4Real: A Real-World Large-Scale Dataset for Vehicle-to-Vehicle Cooperative Perception

Author:

Xu Runsheng1,Xia Xin1,Li Jinlong2,Li Hanzhao1,Zhang Shuo1,Tu Zhengzhong3,Meng Zonglin1,Xiang Hao1,Dong Xiaoyu4,Song Rui5,Yu Hongkai2,Zhou Bolei1,Ma Jiaqi1

Affiliation:

1. University of California,Los Angeles

2. Cleveland State University

3. University of Texas at Austin

4. Northwestern University

5. Technical University of Munich

Publisher

IEEE

Reference58 articles.

1. Unsupervised domain adaptation by backpropagation;ganin;International Conference on Machine Learning,0

2. Cross-view Transformers for real-time Map-view Semantic Segmentation

3. Embracing Single Stride 3D Object Detector with Sparse Transformer

4. Tracking Objects as Pixel-Wise Distributions

5. Collaborative perception in autonomous driving: Methods, datasets and challenges;han;ArXiv Preprint,2023

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2. Image Analysis in Autonomous Vehicles: A Review of the Latest AI Solutions and Their Comparison;Applied Sciences;2024-09-11

3. CooTest: An Automated Testing Approach for V2X Communication Systems;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11

4. Multi-Vehicle Cooperative Simultaneous LiDAR SLAM and Object Tracking in Dynamic Environments;IEEE Transactions on Intelligent Transportation Systems;2024-09

5. BB-Align: A Lightweight Pose Recovery Framework for Vehicle-to-Vehicle Cooperative Perception;2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS);2024-07-23

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