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Paper · 2403.10145 · CVPR · 2024

RCooper: A Real-world Large-scale Dataset for Roadside Cooperative Perception

Haibao Yu, Wenxian Yang, Siqi Fan, Zaiqing Nie, Jirui Yuan, Chenxi Li, Ruiyang Hao, Yingru Dai, Zhenlin Zhang, Yuntian Wang

arXiv · PDF · Open in the Atlas

Code that ran

We lifted 10 functions out of this paper's own repositories and ran 5 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.

RepositoryRoleRan
AIR-THU/DAIR-RCooper canonical 5 of 10
FunctionStatusWhere it lives
GetCross Ran AIR-THU/DAIR-RCooper/codes/ab3dmot_plugin/data_convert/convert_dair_kitti2ab3dmot.py
pointer only (licence: NONE) · get_code("a82735309c370ce0")
dot_product Ran AIR-THU/DAIR-RCooper/codes/ab3dmot_plugin/data_convert/convert_dair_kitti2ab3dmot.py
pointer only (licence: NONE) · get_code("60c3eba478902f5b")
get_files_path Ran AIR-THU/DAIR-RCooper/codes/ab3dmot_plugin/data_convert/coop_label_dair2kitti.py
pointer only (licence: NONE) · get_code("3b7a878ab7286648")
range2box Ran AIR-THU/DAIR-RCooper/codes/ab3dmot_plugin/data_convert/convert_dair_kitti2ab3dmot.py
pointer only (licence: NONE) · get_code("18614f60fc7bbe87")
read_json Ran AIR-THU/DAIR-RCooper/codes/ab3dmot_plugin/data_convert/coop_label_dair2kitti.py
pointer only (licence: NONE) · get_code("4dd25e68caa95a28")
add_sin_difference Not yet run AIR-THU/DAIR-RCooper/codes/opencood_plugin/opencood/loss/ciassd_loss.py
pointer only (licence: NONE) · get_code("725b188cee8a1577")
get_direction_target Not yet run AIR-THU/DAIR-RCooper/codes/opencood_plugin/opencood/loss/ciassd_loss.py
pointer only (licence: NONE) · get_code("71d71587ce799f91")
indices_to_dense_vector Not yet run AIR-THU/DAIR-RCooper/codes/opencood_plugin/opencood/loss/fpvrcnn_loss.py
pointer only (licence: NONE) · get_code("8acab2f0442a1dc3")
one_hot_f Not yet run AIR-THU/DAIR-RCooper/codes/opencood_plugin/opencood/loss/ciassd_loss.py
pointer only (licence: NONE) · get_code("cbb724502b77baff")
weighted_sigmoid_binary_cross_entropy Not yet run AIR-THU/DAIR-RCooper/codes/opencood_plugin/opencood/loss/fpvrcnn_loss.py
pointer only (licence: NONE) · get_code("d6d4a84f040cbc2e")

Repositories linked to this paper

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Abstract

The value of roadside perception, which could extend the boundaries of autonomous driving and traffic management, has gradually become more prominent and acknowledged in recent years. However, existing roadside perception approaches only focus on the single-infrastructure sensor system, which cannot realize a comprehensive understanding of a traffic area because of the limited sensing range and blind spots. Orienting high-quality roadside perception, we need Roadside Cooperative Perception (RCooper) to achieve practical area-coverage roadside perception for restricted traffic areas. Rcooper has its own domain-specific challenges, but further exploration is hindered due to the lack of datasets. We hence release the first real-world, large-scale RCooper dataset to bloom the research on practical roadside cooperative perception, including detection and tracking. The manually annotated dataset comprises 50k images and 30k point clouds, including two representative traffic scenes (i.e., intersection and corridor). The constructed benchmarks prove the effectiveness of roadside cooperation perception and demonstrate the direction of further research. Codes and dataset can be accessed at: https://github.com/AIR-THU/DAIR-RCooper.

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