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Online lane graph construction is a promising but challenging task in autonomous driving.
Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: MICCAI (2015)
2015
Earlier work this paper cites.
He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR (2016)
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
Lin, T., Goyal, P., Girshick, R.B., He, K., Dollár, P.: Focal loss for dense object detection. In: ICCV (2017)
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
Mattyus, G., Luo, W., Urtasun, R.: Deeproadmapper: Extracting road topology from aerial images. In: ICCV (2017)
2017
Earlier work this paper cites.
Bastani, F., He, S., Abbar, S., Alizadeh, M., Balakrishnan, H., Chawla, S., Madden, S., DeWitt, D.: Roadtracer: Automatic extraction of road networks from aerial images. In: CVPR (2018)
2018
Earlier work this paper cites.
Buslaev, A., Seferbekov, S., Iglovikov, V., Shvets, A.: Fully convolutional network for automatic road extraction from satellite imagery. In: CVPR (2018)
2018
Earlier work this paper cites.
Yan, Y., Mao, Y., Li, B.: Second: Sparsely embedded convolutional detection. Sensors 18
2018
Earlier work this paper cites.
Zhou, L., Zhang, C., Wu, M.: D-linknet: Linknet with pretrained encoder and dilated convolution for high resolution satellite imagery road extraction. In: CVPRW (2018)
2018
Earlier work this paper cites.
Batra, A., Singh, S., Pang, G., Basu, S., Jawahar, C., Paluri, M.: Improved road connectivity by joint learning of orientation and segmentation. In: CVPR (2019)
2019
Earlier work this paper cites.
Chu, H., Li, D., Acuna, D., Kar, A., Shugrina, M., Wei, X., Liu, M.Y., Torralba, A., Fidler, S.: Neural turtle graphics for modeling city road layouts. In: ICCV (2019)
2019
Earlier work this paper cites.
Garnett, N., Cohen, R., Pe’er, T., Lahav, R., Levi, D.: 3d-lanenet: end-to-end 3d multiple lane detection. In: ICCV (2019)
2019
Earlier work this paper cites.
Li, Z., Wegner, J.D., Lucchi, A.: Topological map extraction from overhead images. In: ICCV (2019)
2019
Earlier work this paper cites.
Caesar, H., Bankiti, V., Lang, A.H., Vora, S., Liong, V.E., Xu, Q., Krishnan, A., Pan, Y., Baldan, G., Beijbom, O.: nuscenes: A multimodal dataset for autonomous driving. In: CVPR (2020)
2020
Earlier work this paper cites.
Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S.: End-to-end object detection with transformers. In: ECCV (2020)
2020
Earlier work this paper cites.
Guo, Y., Chen, G., Zhao, P., Zhang, W., Miao, J., Wang, J., Choe, T.E.: Gen-lanenet: A generalized and scalable approach for 3d lane detection. In: ECCV (2020)
2020
Earlier work this paper cites.
He, S., Bastani, F., Jagwani, S., Alizadeh, M., Balakrishnan, H., Chawla, S., Elshrif, M.M., Madden, S., Sadeghi, M.A.: Sat2graph: Road graph extraction through graph-tensor encoding. In: ECCV (2020)
2020
Earlier work this paper cites.
Tan, Y.Q., Gao, S.H., Li, X.Y., Cheng, M.M., Ren, B.: Vecroad: Point-based iterative graph exploration for road graphs extraction. In: CVPR (2020)
2020
Earlier work this paper cites.
Can, Y.B., Liniger, A., Paudel, D.P., Van Gool, L.: Structured bird’s-eye-view traffic scene understanding from onboard images. In: ICCV (2021)
2021
Cited alongside, same era.
Fang, Y., Liao, B., Wang, X., Fang, J., Qi, J., Wu, R., Niu, J., Liu, W.: You only look at one sequence: Rethinking transformer in vision through object detection. NeurIPS (2021)
2021
Cited alongside, same era.
Liu, R., Yuan, Z., Liu, T., Xiong, Z.: End-to-end lane shape prediction with transformers. In: WACV (2021)
2021
Cited alongside, same era.
Mi, L., Zhao, H., Nash, C., Jin, X., Gao, J., Sun, C., Schmid, C., Shavit, N., Chai, Y., Anguelov, D.: Hdmapgen: A hierarchical graph generative model of high definition maps. In: CVPR (2021)
2021
Cited alongside, same era.
Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Keep your eyes on the lane: Real-time attention-guided lane detection. In: CVPR (2021)
2022
Later among the works it cites.
Lu, J., Zhou, Z., Zhu, X., Xu, H., Zhang, L.: Learning ego 3d representation as ray tracing. In: ECCV (2022)
2022
Later among the works it cites.
2022
Later among the works it cites.
Wang, J., Ma, Y., Huang, S., Hui, T., Wang, F., Qian, C., Zhang, T.: A keypoint-based global association network for lane detection. In: CVPR (2022)
2022
Later among the works it cites.
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2021
Cited alongside, same era.
Xu, Z., Sun, Y., Liu, M.: icurb: Imitation learning-based detection of road curbs using aerial images for autonomous driving. IEEE Robotics and Automation Letters 6
2021
Cited alongside, same era.
Zhu, X., Su, W., Lu, L., Li, B., Wang, X., Dai, J.: Deformable DETR: deformable transformers for end-to-end object detection. In: ICLR (2021)
2021
Cited alongside, same era.
Can, Y.B., Liniger, A., Paudel, D.P., Van Gool, L.: Topology preserving local road network estimation from single onboard camera image. In: CVPR (2022)
2022
Cited alongside, same era.
Chen, L., Sima, C., Li, Y., Zheng, Z., Xu, J., Geng, X., Li, H., He, C., Shi, J., Qiao, Y., Yan, J.: Persformer: 3d lane detection via perspective transformer and the openlane benchmark. In: ECCV (2022)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Feng, Z., Guo, S., Tan, X., Xu, K., Wang, M., Ma, L.: Rethinking efficient lane detection via curve modeling. In: CVPR (2022)
2022
Cited alongside, same era.
He, S., Balakrishnan, H.: Lane-level street map extraction from aerial imagery. In: WACV (2022)
2022
Cited alongside, same era.
2022
Later among the works it cites.
Zhou, B., Krähenbühl, P.: Cross-view transformers for real-time map-view semantic segmentation. In: CVPR (2022)
2022
Later among the works it cites.
Büchner, M., Zürn, J., Todoran, I.G., Valada, A., Burgard, W.: Learning and aggregating lane graphs for urban automated driving. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 13415–13424 (2023)
2023
Closest in time.
Dauner, D., Hallgarten, M., Geiger, A., Chitta, K.: Parting with misconceptions about learning-based vehicle motion planning. In: Conference on Robot Learning (CoRL) (2023)
2023
Closest in time.
Ding, W., Qiao, L., Qiu, X., Zhang, C.: Pivotnet: Vectorized pivot learning for end-to-end hd map construction. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 3672–3682 (2023)
2023
Closest in time.
Jiang, B., Chen, S., Xu, Q., Liao, B., Chen, J., Zhou, H., Zhang, Q., Liu, W., Huang, C., Wang, X.: Vad: Vectorized scene representation for efficient autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 8340–8350 (2023)
2023
Closest in time.
2023
Closest in time.
Liao, B., Chen, S., Wang, X., Cheng, T., Zhang, Q., Liu, W., Huang, C.: MapTR: Structured modeling and learning for online vectorized HD map construction. In: ICLR (2023), https://openreview.net/forum?id=k7p_YAO7yE
2023
Closest in time.
Qiao, L., Ding, W., Qiu, X., Zhang, C.: End-to-end vectorized hd-map construction with piecewise bezier curve. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 13218–13228 (2023)
2023
Closest in time.
2023
Closest in time.
Wang, H., Li, T., Li, Y., Chen, L., Sima, C., Liu, Z., Wang, B., Jia, P., Wang, Y., Jiang, S., Wen, F., Xu, H., Luo, P., Yan, J., Zhang, W., Li, H.: Openlane-v2: A topology reasoning benchmark for unified 3d hd mapping. In: NeurIPS (2023)
2023
Closest in time.
2023
Closest in time.
Wu, D., Chang, J., Jia, F., Liu, Y., Wang, T., Shen, J.: TopoMLP: An simple yet strong pipeline for driving topology reasoning. In: The Twelfth International Conference on Learning Representations (2024), https://openreview.net/forum?id=0gTW5JUFTW
2024
Closest in time.
Yuan, T., Liu, Y., Wang, Y., Wang, Y., Zhao, H.: Streammapnet: Streaming mapping network for vectorized online hd map construction. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 7356–7365 (2024)
2024
Closest in time.