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Collaborative_Perception

This repository is a paper digest of recent advances in collaborative / cooperative / multi-agent perception for V2I / V2V / V2X autonomous driving scenario.
https://github.com/Little-Podi/Collaborative_Perception

Last synced: 12 days ago
JSON representation

  • :bookmark:Method and Framework

  • :star2:Recommendation

    • Helpful Learning Resource:thumbsup::thumbsup::thumbsup:

      • [paper - to-Everything Autonomous Driving: A Survey on Collaborative Perception [[paper](https://arxiv.org/abs/2308.16714)], Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges [[paper](https://arxiv.org/abs/2301.06262)], A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation [[paper](https://arxiv.org/abs/2208.10590)]
      • [video - Driving [[video](https://youtu.be/WUDxYn7QtJU)], When Vision Transformers Meet Cooperative Perception [[video](https://youtu.be/rLAU4eqoOIU)], Scene Understanding beyond the Visible [[video](https://youtu.be/oz0AnmJZCR4)], Robust Collaborative Perception against Communication Interruption [[video](https://youtu.be/3cIWpMrsyeE)], Collaborative and Adversarial 3D Perception for Autonomous Driving [[video](https://youtu.be/W-AONQMfGi0)], Vehicle-to-Vehicle Communication for Self-Driving [[video](https://youtu.be/oikdOpmIoc4)], Adversarial Robustness for Self-Driving [[video](https://youtu.be/8uBFXzyII5Y)], L4感知系统的终极形态：协同驾驶 [[video](https://youtu.be/NvixMEDHht4)], CoBEVFlow-解决车-车/路协同感知的时序异步问题 [[video](https://youtu.be/IBTgalAjye8)], 新一代协作感知Where2comm减少通信带宽十万倍 [[video](https://youtu.be/i5coMk4hkuk)], 从任务相关到任务无关的多机器人协同感知 [[video](https://course.zhidx.com/c/MDlkZjcyZDgwZWI4ODBhOGQ4MzM=)], 协同自动驾驶：仿真与感知 [[video](https://course.zhidx.com/c/MmQ1YWUyMzM1M2I3YzVlZjE1NzM=)], 基于群体协作的超视距态势感知 [[video](https://www.koushare.com/video/videodetail/33015)]
      • [web - page.github.io)], Zixing Lei@SJTU [[web](https://chezacar.github.io)], Yifan Lu@SJTU [[web](https://yifanlu0227.github.io)], Siqi Fan@THU [[web](https://leofansq.github.io)], Hang Qiu@Waymo [[web](https://hangqiu.github.io)], Dian Chen@UT Austin [[web](https://www.cs.utexas.edu/~dchen)], Yen-Cheng Liu@GaTech [[web](https://ycliu93.github.io)], Tsun-Hsuan Wang@MIT [[web](https://zswang666.github.io)]
      • [web
      • [video - Aware Communication for Multi-Agent Reinforcement Learning [[video](https://youtu.be/YBgW2oA_n3k)], A Survey of Multi-Agent Reinforcement Learning with Communication [[paper](https://arxiv.org/abs/2203.08975)]
      • [code - mobility/OpenCDA)] [[doc](https://opencda-documentation.readthedocs.io/en/latest)]
      • [video - to-Vehicle (V2V) Communication (Waabi CVPR 23 Tutorial on Self-Driving Cars) [[video](https://youtu.be/T-N51B8mZB8)], The Ultimate Solution for L4 Autonomous Driving [[video](https://youtu.be/cyNxemm4Ujg)], When Vision Transformers Meet Cooperative Perception [[video](https://youtu.be/rLAU4eqoOIU)], Scene Understanding beyond the Visible [[video](https://youtu.be/oz0AnmJZCR4)], Robust Collaborative Perception against Communication Interruption [[video](https://youtu.be/3cIWpMrsyeE)], Collaborative and Adversarial 3D Perception for Autonomous Driving [[video](https://youtu.be/W-AONQMfGi0)], Vehicle-to-Vehicle Communication for Self-Driving [[video](https://youtu.be/oikdOpmIoc4)], Adversarial Robustness for Self-Driving [[video](https://youtu.be/8uBFXzyII5Y)], L4感知系统的终极形态：协同驾驶 [[video](https://youtu.be/NvixMEDHht4)], CoBEVFlow-解决车-车/路协同感知的时序异步问题 [[video](https://youtu.be/IBTgalAjye8)], 新一代协作感知Where2comm减少通信带宽十万倍 [[video](https://youtu.be/i5coMk4hkuk)], 从任务相关到任务无关的多机器人协同感知 [[video](https://course.zhidx.com/c/MDlkZjcyZDgwZWI4ODBhOGQ4MzM=)], 协同自动驾驶：仿真与感知 [[video](https://course.zhidx.com/c/MmQ1YWUyMzM1M2I3YzVlZjE1NzM=)], 基于群体协作的超视距态势感知 [[video](https://www.koushare.com/video/videodetail/33015)]
      • [web
      • [video - Aware Communication for Multi-Agent Reinforcement Learning [[video](https://youtu.be/YBgW2oA_n3k)], A Survey of Multi-Agent Reinforcement Learning with Communication [[paper](https://arxiv.org/abs/2203.08975)]
      • [paper - to-Everything Autonomous Driving: A Survey on Collaborative Perception [[paper](https://arxiv.org/abs/2308.16714)], Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges [[paper](https://arxiv.org/abs/2301.06262)], A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation [[paper](https://arxiv.org/abs/2208.10590)]
      • [paper - to-Everything Autonomous Driving: A Survey on Collaborative Perception [[paper](https://arxiv.org/abs/2308.16714)], Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges [[paper](https://arxiv.org/abs/2301.06262)], A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation [[paper](https://arxiv.org/abs/2208.10590)]
      • [paper - to-Everything Autonomous Driving: A Survey on Collaborative Perception [[paper](https://arxiv.org/abs/2308.16714)], Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges [[paper](https://arxiv.org/abs/2301.06262)], A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation [[paper](https://arxiv.org/abs/2208.10590)]
      • [paper - to-End V2X Cooperative Autonomous Driving Competition [[paper](https://arxiv.org/abs/2507.21610)], Automated Vehicles Should be Connected with Natural Language [[paper](https://arxiv.org/abs/2507.01059)], Collaborative Perception Datasets for Autonomous Driving: A Review [[paper](https://arxiv.org/abs/2504.12696)], Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunities [[paper](https://arxiv.org/abs/2401.01544)], V2X Cooperative Perception for Autonomous Driving: Recent Advances and Challenges [[paper](https://arxiv.org/abs/2310.03525)], Towards Vehicle-to-Everything Autonomous Driving: A Survey on Collaborative Perception [[paper](https://arxiv.org/abs/2308.16714)], Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges [[paper](https://arxiv.org/abs/2301.06262)], A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation [[paper](https://arxiv.org/abs/2208.10590)]
      • [video - to-Vehicle (V2V) Communication (Waabi CVPR 23 Tutorial on Self-Driving Cars) [[video](https://youtu.be/T-N51B8mZB8)], The Ultimate Solution for L4 Autonomous Driving [[video](https://youtu.be/cyNxemm4Ujg)], When Vision Transformers Meet Cooperative Perception [[video](https://youtu.be/rLAU4eqoOIU)], Scene Understanding beyond the Visible [[video](https://youtu.be/oz0AnmJZCR4)], Robust Collaborative Perception against Communication Interruption [[video](https://youtu.be/3cIWpMrsyeE)], Collaborative and Adversarial 3D Perception for Autonomous Driving [[video](https://youtu.be/W-AONQMfGi0)], Vehicle-to-Vehicle Communication for Self-Driving [[video](https://youtu.be/oikdOpmIoc4)], Adversarial Robustness for Self-Driving [[video](https://youtu.be/8uBFXzyII5Y)], L4感知系统的终极形态：协同驾驶 [[video](https://youtu.be/NvixMEDHht4)], CoBEVFlow-解决车-车/路协同感知的时序异步问题 [[video](https://youtu.be/IBTgalAjye8)], 新一代协作感知Where2comm减少通信带宽十万倍 [[video](https://youtu.be/i5coMk4hkuk)], 从任务相关到任务无关的多机器人协同感知 [[video](https://course.zhidx.com/c/MDlkZjcyZDgwZWI4ODBhOGQ4MzM=)], 协同自动驾驶：仿真与感知 [[video](https://course.zhidx.com/c/MmQ1YWUyMzM1M2I3YzVlZjE1NzM=)], 基于群体协作的超视距态势感知 [[video](https://www.koushare.com/video/videodetail/33015)]
      • [video - Aware Communication for Multi-Agent Reinforcement Learning [[video](https://youtu.be/YBgW2oA_n3k)], A Survey of Multi-Agent Reinforcement Learning with Communication [[paper](https://arxiv.org/abs/2203.08975)]
      • [paper - to-End V2X Cooperative Autonomous Driving Competition [[paper](https://arxiv.org/abs/2507.21610)], Automated Vehicles Should be Connected with Natural Language [[paper](https://arxiv.org/abs/2507.01059)], Collaborative Perception Datasets for Autonomous Driving: A Review [[paper](https://arxiv.org/abs/2504.12696)], Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunities [[paper](https://arxiv.org/abs/2401.01544)], V2X Cooperative Perception for Autonomous Driving: Recent Advances and Challenges [[paper](https://arxiv.org/abs/2310.03525)], Towards Vehicle-to-Everything Autonomous Driving: A Survey on Collaborative Perception [[paper](https://arxiv.org/abs/2308.16714)], Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges [[paper](https://arxiv.org/abs/2301.06262)], A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation [[paper](https://arxiv.org/abs/2208.10590)]
      • [web
Programming Languages
Python 3
Categories
:bookmark:Method and Framework 160 :bookmark:Dataset and Simulator 53 :star2:Recommendation 17
Sub Categories
Selected Preprint 89 Helpful Learning Resource:thumbsup::thumbsup::thumbsup: 17 CVPR 2025 10 ICRA 2023 9 CVPR 2024 8 CVPR 2026 7 ICCV 2023 7 ICCV 2025 6 AAAI 2026 6 NeurIPS 2025 5 ICRA 2025 5 CVPR 2023 4 AAAI 2025 4 AAAI 2024 3 IROS 2025 3 ICLR 2025 3 CVPR 2022 3 NeurIPS 2023 3 MM 2023 3 ECCV 2024 3 CoRL 2022 2 ICRA 2020 2 ECCV 2020 2 ICRA 2024 2 ICCV 2021 2 ECCV 2022 2 ICRA 2022 2 NeurIPS 2021 1 IROS 2021 1 ICLR 2023 1 NeurIPS 2024 1 WACV 2026 1 CoRL 2023 1 CVPR 2020 1 ICLR 2024 1 ACCV 2022 1 WACV 2023 1 MM 2025 1 IJCAI 2022 1 WACV 2024 1 ICLR 2026 1 NeurIPS 2022 1 CoRL 2017 1 MM 2022 1 CoRL 2020 1
Keywords
self-driving 1 nerf 1 multimodal-deep-learning 1 multiagent 1 dataset 1 cvpr2024 1 coperception 1 collaborative-perception 1 3dgs 1