% Long form of conference & journal abbreviations -- especially for camera ready
@String(PAMI  = {IEEE Trans. Pattern Anal. Mach. Intell.})
@String(IJCV  = {Int. J. Comput. Vis.})
@String(CVPR  = {IEEE Conf. Comput. Vis. Pattern Recog.})
@String(ICCV  = {Int. Conf. Comput. Vis.})
@String(ECCV  = {Eur. Conf. Comput. Vis.})
@String(NeurIPS = {Adv. Neural Inform. Process. Syst.})
@String(ICML  = {Int. Conf. Mach. Learn.})
@String(ICLR  = {Int. Conf. Learn. Represent.})
@String(ACCV  = {Asian Conf. Comput. Vis.})
@String(BMVC  = {Brit. Mach. Vis. Conf.})
@String(CVPRW = {IEEE Conf. Comput. Vis. Pattern Recog. Worksh.})
@String(AAAI  = {AAAI})
@String(IJCAI = {IJCAI})
@String(ICIP  = {IEEE Int. Conf. Image Process.})
@String(ICPR  = {Int. Conf. Pattern Recog.})
@String(ICASSP=	{ICASSP})
@String(ICME  = {Int. Conf. Multimedia and Expo})
@String(JMLR  = {J. Mach. Learn. Res.})
@String(TMLR  = {Trans. Mach. Learn Res.})
@String(TOG   = {ACM Trans. Graph.})
@String(TIP   = {IEEE Trans. Image Process.})
@String(TVCG  = {IEEE Trans. Vis. Comput. Graph.})
@String(TCSVT = {IEEE Trans. Circuit Syst. Video Technol.})
@String(TMM   = {IEEE Trans. Multimedia})
@String(ACMMM = {ACM Int. Conf. Multimedia})
@String(PR    = {Pattern Recognition})

@String(MNI	  = {Nature Mach. Intell.})
@String(SPL	  = {IEEE Sign. Process. Letters})
@String(VR    = {Vis. Res.})
@String(JOV	  = {J. Vis.})
@String(TVC   = {The Vis. Comput.})
@String(JCST  = {J. Comput. Sci. Tech.})
@String(CGF   = {Comput. Graph. Forum})
@String(CVM   = {Computational Visual Media})


% Short form of conference & journal abbreviations -- especially for submission version
% if desired, remove these macros in favor of the above ones
@String(PAMI  = {IEEE TPAMI})
@String(IJCV  = {IJCV})
@String(CVPR  = {CVPR})
@String(ICCV  = {ICCV})
@String(ECCV  = {ECCV})
@String(NeurIPS = {NeurIPS})
@String(ICML  = {ICML})
@String(ICLR  = {ICLR})
@String(ACCV  = {ACCV})
@String(BMVC  =	{BMVC})
@String(CVPRW = {CVPRW})
@String(AAAI  = {AAAI})
@String(IJCAI = {IJCAI})
@String(ICIP  = {ICIP})
@String(ICPR  = {ICPR})
@String(ICASSP=	{ICASSP})
@String(ICME  =	{ICME})
@String(JMLR  = {JMLR})
@String(TMLR  = {TMLR})
@String(TOG   = {ACM TOG})
@String(TIP   = {IEEE TIP})
@String(TVCG  = {IEEE TVCG})
@String(TCSVT = {IEEE TCSVT})
@String(TMM   =	{IEEE TMM})
@String(ACMMM = {ACM MM})
@String(PR    = {PR})

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  author = {Sun, Pei and Kretzschmar, Henrik and Dotiwalla, Xerxes and Chouard, Aurélien and Patnaik, Vijay and Tsui, Praveen and Guo, Jingyu and Zhou, Yin and Chai, Yuning and Caine, Benjamin and others},
  title = {Scalability in Perception for Autonomous Driving: Waymo Open Dataset},
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  year = {2020}
}

@inproceedings{nuscenes,
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  title = {nuscenes: A Multimodal Dataset for Autonomous Driving},
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}

@inproceedings{kitti,
  author = {Geiger, Andreas and Lenz, Philip and Urtasun, Raquel},
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@article{v2xsim2022,
  author = {Li, Yuxuan and An, Ziqi and Wang, Zikun and Zhong, Yikun and Chen, Shuang and Feng, Chen},
  title = {V2X-Sim: A Virtual Collaborative Perception Dataset for Autonomous Driving},
  journal = {arXiv preprint arXiv:2202.08449},
  year = {2022},
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@inproceedings{motiondiversification2024,
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@inproceedings{opv2v2022,
  author = {Xu, Rong and Xiang, Hongsheng and Xia, Xiaoyu and Han, Xinyue and Li, Jie and Ma, Jiaqi},
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  year = {2022}
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    title = {Computer Vision -- ACCV 2020},
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}

@inproceedings{2021waymomotion,
  author = {Ettinger, Scott and Cheng, Shuyang and Caine, Benjamin and Liu, Chenxi and Zhao, Hang and Pradhan, Sabeek and Chai, Yuning and Sapp, Ben and Qi, Charles R. and Zhou, Yin and others},
  title = {Large Scale Interactive Motion Forecasting for Autonomous Driving: The Waymo Open Motion Dataset},
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  year = {2021}
}

@article{2023boreas,
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@article{2023argoverse,
  author = {Wilson, Benjamin and Qi, William and Agarwal, Tanmay and Lambert, John and Singh, Jagjeet and Khandelwal, Siddhesh and Pan, Bowen and Kumar, Ratnesh and others},
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@inproceedings{2020bdd100k,
  author = {Yu, Fisher and Chen, Haofeng and Wang, Xin and Xian, Wenqi and Chen, Yingying and Liu, Fangchen and Madhavan, Vashisht and Darrell, Trevor},
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}

@misc{2022v2xsim,
  author = {Li, Yuxuan and An, Ziqi and Wang, Zikun and Zhong, Yikun and Chen, Shuang and Feng, Chen},
  title = {V2X-Sim: A Virtual Collaborative Perception Dataset for Autonomous Driving},
  year = {2022},
  howpublished = {\url{https://arxiv.org/abs/2202.08449}}
}

@misc{2021opv2v,
  author = {Xu, Rong and Xiang, Hongsheng and Xia, Xiaoyu and Han, Xinyue and Li, Jie and Ma, Jiaqi},
  title = {Opv2v: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication},
  year = {2021},
  howpublished = {\url{https://arxiv.org/abs/2109.07644}}
}

@inproceedings{2022dairv2x,
  author = {Yu, Hang and Luo, Yisheng and Shu, Mengshi and Huo, Yawen and Yang, Zhenpeng and Shi, Yi and Guo, Zhi and Li, Hui and Hu, Xiaoyu and Yuan, Junsong and others},
  title = {Dair-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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  year = {2022}
}

@inproceedings{2023Wayve-gaia1,
  author = {Hu, Anthony and Russell, Lloyd and Yeo, Hudson and Murez, Zak and Fedoseev, George and Kendall, Alex and Shotton, Jamie and Corrado, Gianluca},
  title = {GAIA-1: A Generative World Model for Autonomous Driving},
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  url = {https://arxiv.org/abs/2309.17080}
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@inproceedings{2009automaticDet-RW,
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@inproceedings{cheng2022masked,
  title={Masked-attention Mask Transformer for Universal Image Segmentation},
  author={Cheng, Bowen and Misra, Ishan and Schwing, Alexander G and Kirillov, Alexander and Girdhar, Rohit},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2022}
}

@inproceedings{cheng2022pointly,
  title={Pointly-Supervised Instance Segmentation},
  author={Cheng, Bowen and Parkhi, Omkar and Kirillov, Alexander},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2022}
}

@inproceedings{ghiasi2022simple,
  title={Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation},
  author={Ghiasi, Golnaz and Cui, Yin and Srinivas, Aravind and Qian, Rui and Lin, TsungYi and Cubuk, Ekin D and Le, Quoc V and Zoph, Barret},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2022}
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@inproceedings{hoyer2022daformer,
  title={Daformer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation},
  author={Hoyer, Lukas and Dai, Dengxin and Van Gool, Luc},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2022}
}

@inproceedings{sakaridis2019guided,
  title={Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation},
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  booktitle={ICCV},
  year={2019}
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@inproceedings{xu2023open,
  title={Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models},
  author={Xu, Jiarui and Liu, Sifei and Vahdat, Arash and Byeon, Wonmin and Wang, Xiaolong and De Mello, Shalini},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2023}
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@inproceedings{zhang2023simple,
  title={A Simple Framework for Open-Vocabulary Segmentation and Detection},
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@inproceedings{kim2019detection,
title={Detection of construction areas in road environments using deep learning},
author={Kim, Jongwon and Park, Jihun and Kim, Sungho},
booktitle={IEEE Transactions on Intelligent Transportation Systems},
year={2019}
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@inproceedings{wang2020roadworks,
title={RoadWorks-Net: A real-time semantic segmentation network for road construction zone detection},
author={Wang, Xue and Li, Yu and Zhang, Hao},
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year={2020}
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@inproceedings{chen2021attention,
title={Attention-guided construction zone segmentation for autonomous driving},
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@inproceedings{li2019attentive,
title={Line-CNN: End-to-End Traffic Line Detection With Line Proposal Unit},
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year={2019}
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@inproceedings{zhou2020da,
title={DA-RoadSeg: Diverse Annotation for Real-time Road Segmentation},
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year={2020}
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@inproceedings{kong2020seanet,
title={SEANet: Semantic Embedding Attention Network for Road Detection},
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year={2020}
}

@inproceedings{fan2020learning,
title={Learning Collision-Free Space Detection from Stereo Images: Homography Matrix Brings Better Data Augmentation},
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year={2020}
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@inproceedings{chen2020progressive,
title={DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs},
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year={2020}
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@inproceedings{tao2020hierarchical,
title={Hierarchical Multi-Scale Attention for Semantic Segmentation},
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year={2020}
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@inproceedings{zhu2019improving,
title={Improving Semantic Segmentation via Video Propagation and Label Relaxation},
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@inproceedings{yu2020bdd100k,
title={BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning},
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@inproceedings{wang2019apolloscape,
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year={2019}
}

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@article{ultralytics2023yolov8,
  title={YOLOv8: A High-Performance Object Detection and Segmentation Model},
  author={Jocher, Glenn and Chaurasia, Ayush and Qiu, Jing},
  journal={arXiv preprint arXiv:2305.09972},
  year={2023}
}

@article{ultralytics2023yolov8world,
  title={YOLOv8-World: A Real-Time Global Object Detection and Segmentation Model},
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  year={2023}
}

@article{kirillov2023segment,
  title={Segment Anything},
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}

@misc{inavi_qxd5000,
  title = {INAVI QXD5000 Black Box},
  author = {{INAVI}},
  year = {2024},
  note = {Product Specification},
  howpublished = {\url{https://www.inavi.com/Products/BlackBox/Gate?target=_QXD5000}},
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}

@inproceedings{Ghosh2024ROADWork,
  author = {Ghosh, Anurag and Tamburo, Robert and Zheng, Shen and Alvarez-Padilla, Juan R. and Zhu, Hailiang and Cardei, Michael and Dunn, Nicholas and Mertz, Christoph and Narasimhan, Srinivasa G.},
  title = {ROADWork Dataset: Learning to Recognize, Observe, Analyze and Drive Through Work Zones},
  booktitle = {TBD},
  year = {2024},
  publisher = {Carnegie Mellon University},
  url = {https://www.cs.cmu.edu/~ILIM/roadwork_dataset}
}

@article{ETLi,
    author = {Kang, Jungyu and Han, Seung-Jun and Kim, Nahyeon and Min, Kyoung-Wook},
    title = {ETLi: Efficiently annotated traffic LiDAR dataset using incremental and suggestive annotation},
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    year = {2021},
    month = {September},
    day = {24},
    doi = {https://doi.org/10.4218/etrij.2021-0055},
}

@article{EMOS,
    author = {Lee, Dongjin and Han, Seung-Jun and Min, Kyoung-Wook and Choi, Jungdan and Park, Cheong Hee},
    title = {EMOS: Enhanced moving object detection and classification via sensor fusion and noise filtering},
    journal = {ETRI Journal},
    year = {2023},
    month = {September},
    day = {25},
    doi = {https://doi.org/10.4218/etrij.2023-0109},
}

@article{An2023CRFNet,
    author = {An, Taeghyun and Kang, Jungyu and Choi, Dooseop and Min, Kyoung-Wook},
    title = {CRFNet: Context ReFInement Network used for semantic segmentation},
    journal = {ETRI Journal},
    year = {2023},
    month = {October},
    day = {4},
    doi = {10.4218/etrij.2023-0017},
}