V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecasting
Author:
Affiliation:
1. Institute for AI Industry Research (AIR), Tsinghua University
2. Baidu Inc.
3. Beijing Connected and Autonomous Vehicles Technology Co., Ltd
4. The University of Hong Kong
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10204878.pdf?arnumber=10204878
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4. Argoverse 2: Next generation datasets for self-driving perception and forecasting;wilson;Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2),0
5. Where2comm: Communication-efficient collaborative perception via spatial confidence maps;hu;Advances in neural information processing systems,2022
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1. DAnoScenE: a driving anomaly scenario extraction framework for autonomous vehicles in urban streets;Journal of Intelligent Transportation Systems;2023-12-14
2. Collaborative Perception in Autonomous Driving: Methods, Datasets, and Challenges;IEEE Intelligent Transportation Systems Magazine;2023-11
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