The code will be made publicly available upon publication of the paper. Below are selected experimental results from the manuscript, shown here for illustrative purposes only. The 3D bounding boxes in red and green depict the prediction and the ground truth, respectively.

Fig.1: BEV View Demo from V2V4Real

Fig.2: SV View Demo from V2V4Real

Fig.3: BEV View Demo from V2XSet

Fig.4: SV View Demo from V2XSet

[1] R. Xu, X. Xia, J. Li, H. Li, S. Zhang, Z. Tu, Z. Meng, H. Xiang, X. Dong, R. Song, H. Yu, B. Zhou, J. Ma. V2V4Real: A Real-World Large-Scale Dataset for Vehicle-to-Vehicle Cooperative Perception. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13712–13722. IEEE, Vancouver, BC, Canada, 2023.

[2] R. Xu, Z. Tu, H. Xiang, W. Shao, B. Zhou, J. Ma. CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers. In Proceedings of The 6th Conference on Robot Learning, pp. 989-1000. PMLR, 2022.

[3] R. Xu, H. Xiang, Z. Tu, X. Xia, M.-H. Yang, J. Ma. V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer. In Computer Vision — ECCV 2022, pp. 107-124. Springer Nature Switzerland, Cham, 2022.