Fetching the paper…
Reading the bibliography…
End-to-end autonomous driving has witnessed remarkable progress.
Muller, U., Ben, J., Cosatto, E., Flepp, B., Cun, Y.: Off-road obstacle avoidance through end-to-end learning. Advances in neural information processing systems 18
2005
Earlier work this paper cites.
Dong, Y., Hu, Z., Uchimura, K., Murayama, N.: Driver inattention monitoring system for intelligent vehicles: A review. IEEE transactions on intelligent transportation systems 12
2010
Earlier work this paper cites.
Alletto, S., Palazzi, A., Solera, F., Calderara, S., Cucchiara, R.: Dr (eye) ve: a dataset for attention-based tasks with applications to autonomous and assisted driving. In: Proceedings of the ieee conference on computer vision and pattern recognition workshops. pp. 54–60 (2016)
2016
Earlier work this paper cites.
Ba, J.L., Kiros, J.R., Hinton, G.E.: Layer normalization. arXiv preprint arXiv:1607.06450 (2016)
2016
Earlier work this paper cites.
Gaidon, A., Wang, Q., Cabon, Y., Vig, E.: Virtual worlds as proxy for multi-object tracking analysis. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 4340–4349 (2016)
2016
Earlier work this paper cites.
He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 770–778 (2016)
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
Chen, X., Ma, H., Wan, J., Li, B., Xia, T.: Multi-view 3d object detection network for autonomous driving. In: Proceedings of the IEEE conference on Computer Vision and Pattern Recognition. pp. 1907–1915 (2017)
2017
Earlier work this paper cites.
Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., Koltun, V.: Carla: An open urban driving simulator. In: Conference on robot learning. pp. 1–16. PMLR (2017)
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
Tawari, A., Kang, B.: A computational framework for driver’s visual attention using a fully convolutional architecture. In: 2017 IEEE Intelligent Vehicles Symposium (IV). pp. 887–894. IEEE (2017)
2017
Earlier work this paper cites.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
Casas, S., Luo, W., Urtasun, R.: Intentnet: Learning to predict intention from raw sensor data. In: Conference on Robot Learning. pp. 947–956. PMLR (2018)
2018
Earlier work this paper cites.
Ku, J., Mozifian, M., Lee, J., Harakeh, A., Waslander, S.L.: Joint 3d proposal generation and object detection from view aggregation. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 1–8. IEEE (2018)
2018
Earlier work this paper cites.
Liang, M., Yang, B., Wang, S., Urtasun, R.: Deep continuous fusion for multi-sensor 3d object detection. In: Proceedings of the European conference on computer vision (ECCV). pp. 641–656 (2018)
2018
Earlier work this paper cites.
Luo, W., Yang, B., Urtasun, R.: Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net. In: Proceedings of the IEEE conference on Computer Vision and Pattern Recognition. pp. 3569–3577 (2018)
2018
Earlier work this paper cites.
Martin, S., Vora, S., Yuen, K., Trivedi, M.M.: Dynamics of driver’s gaze: Explorations in behavior modeling and maneuver prediction. IEEE Transactions on Intelligent Vehicles 3
2018
Earlier work this paper cites.
Palazzi, A., Abati, D., Solera, F., Cucchiara, R., et al.: Predicting the driver’s focus of attention: the dr (eye) ve project. IEEE transactions on pattern analysis and machine intelligence 41
2018
Earlier work this paper cites.
Qi, X., Chen, Q., Jia, J., Koltun, V.: Semi-parametric image synthesis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 8808–8816 (2018)
2018
Earlier work this paper cites.
Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.C.: Mobilenetv2: Inverted residuals and linear bottlenecks. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 4510–4520 (2018)
2018
Earlier work this paper cites.
Sauer, A., Savinov, N., Geiger, A.: Conditional affordance learning for driving in urban environments. In: Conference on Robot Learning. pp. 237–252. PMLR (2018)
2018
Earlier work this paper cites.
Sobh, I., Amin, L., Abdelkarim, S., Elmadawy, K., Saeed, M., Abdeltawab, O., Gamal, M., El Sallab, A.: End-to-end multi-modal sensors fusion system for urban automated driving (2018)
2018
Earlier work this paper cites.
Antin, J.F., Lee, S., Perez, M.A., Dingus, T.A., Hankey, J.M., Brach, A.: Second strategic highway research program naturalistic driving study methods. Safety Science 119
2019
Earlier work this paper cites.
Codevilla, F., Santana, E., López, A.M., Gaidon, A.: Exploring the limitations of behavior cloning for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 9329–9338 (2019)
2019
Earlier work this paper cites.
Deng, T., Yan, H., Qin, L., Ngo, T., Manjunath, B.: How do drivers allocate their potential attention? driving fixation prediction via convolutional neural networks. IEEE Transactions on Intelligent Transportation Systems 21
2019
Earlier work this paper cites.
Fang, J., Yan, D., Qiao, J., Xue, J., Wang, H., Li, S.: Dada-2000: Can driving accident be predicted by driver attentionf analyzed by a benchmark. In: 2019 IEEE Intelligent Transportation Systems Conference (ITSC). pp. 4303–4309. IEEE (2019)
2019
Earlier work this paper cites.
Liang, M., Yang, B., Chen, Y., Hu, R., Urtasun, R.: Multi-task multi-sensor fusion for 3d object detection. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7345–7353 (2019)
2019
Earlier work this paper cites.
Meyer, G.P., Charland, J., Hegde, D., Laddha, A., Vallespi-Gonzalez, C.: Sensor fusion for joint 3d object detection and semantic segmentation. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition workshops. pp. 0–0 (2019)
2019
Cited alongside, same era.
Rhinehart, N., McAllister, R., Kitani, K., Levine, S.: Precog: Prediction conditioned on goals in visual multi-agent settings. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2821–2830 (2019)
2019
Cited alongside, same era.
Wang, D., Devin, C., Cai, Q.Z., Krähenbühl, P., Darrell, T.: Monocular plan view networks for autonomous driving. In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 2876–2883. IEEE (2019)
2019
Cited alongside, same era.
Xia, Y., Zhang, D., Kim, J., Nakayama, K., Zipser, K., Whitney, D.: Predicting driver attention in critical situations. In: Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers, Part V 14. pp. 658–674. Springer (2019)
Prakash, A., Chitta, K., Geiger, A.: Multi-modal fusion transformer for end-to-end autonomous driving. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7077–7087 (2021)
2021
Later among the works it cites.
Zhang, Z., Liniger, A., Dai, D., Yu, F., Van Gool, L.: End-to-end urban driving by imitating a reinforcement learning coach. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 15222–15232 (2021)
2021
Later among the works it cites.
Chen, D., Krähenbühl, P.: Learning from all vehicles. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 17222–17231 (2022)
2022
Later among the works it cites.
Chitta, K., Prakash, A., Jaeger, B., Yu, Z., Renz, K., Geiger, A.: Transfuser: Imitation with transformer-based sensor fusion for autonomous driving. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022)
2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2019
Cited alongside, same era.
Xing, Y., Lv, C., Wang, H., Wang, H., Ai, Y., Cao, D., Velenis, E., Wang, F.Y.: Driver lane change intention inference for intelligent vehicles: Framework, survey, and challenges. IEEE Transactions on Vehicular Technology 68
2019
Cited alongside, same era.
Behl, A., Chitta, K., Prakash, A., Ohn-Bar, E., Geiger, A.: Label efficient visual abstractions for autonomous driving. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 2338–2345. IEEE (2020)
2020
Cited alongside, same era.
Casas, S., Gulino, C., Liao, R., Urtasun, R.: Spagnn: Spatially-aware graph neural networks for relational behavior forecasting from sensor data. In: 2020 IEEE International Conference on Robotics and Automation (ICRA). pp. 9491–9497. IEEE (2020)
2020
Cited alongside, same era.
Chen, D., Zhou, B., Koltun, V., Krähenbühl, P.: Learning by cheating. In: Conference on Robot Learning. pp. 66–75. PMLR (2020)
2020
Cited alongside, same era.
Chen, K., Oldja, R., Smolyanskiy, N., Birchfield, S., Popov, A., Wehr, D., Eden, I., Pehserl, J.: Mvlidarnet: Real-time multi-class scene understanding for autonomous driving using multiple views. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 2288–2294. IEEE (2020)
2020
Cited alongside, same era.
Droste, R., Jiao, J., Noble, J.A.: Unified image and video saliency modeling. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part V 16. pp. 419–435. Springer (2020)
2020
Cited alongside, same era.
Filos, A., Tigkas, P., McAllister, R., Rhinehart, N., Levine, S., Gal, Y.: Can autonomous vehicles identify, recover from, and adapt to distribution shifts? In: International Conference on Machine Learning. pp. 3145–3153. PMLR (2020)
2020
Cited alongside, same era.
Liang, M., Yang, B., Zeng, W., Chen, Y., Hu, R., Casas, S., Urtasun, R.: Pnpnet: End-to-end perception and prediction with tracking in the loop. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 11553–11562 (2020)
2020
Cited alongside, same era.
Fadadu, S., Pandey, S., Hegde, D., Shi, Y., Chou, F.C., Djuric, N., Vallespi-Gonzalez, C.: Multi-view fusion of sensor data for improved perception and prediction in autonomous driving. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 2349–2357 (2022)
2022
Later among the works it cites.
Gan, S., Pei, X., Ge, Y., Wang, Q., Shang, S., Li, S.E., Nie, B.: Multisource adaption for driver attention prediction in arbitrary driving scenes. IEEE transactions on intelligent transportation systems 23
2022
Later among the works it cites.
Hu, A., Corrado, G., Griffiths, N., Murez, Z., Gurau, C., Yeo, H., Kendall, A., Cipolla, R., Shotton, J.: Model-based imitation learning for urban driving. Advances in Neural Information Processing Systems 35
2022
Later among the works it cites.
Huang, P.J., Lu, C.A., Chen, K.W.: Temporally-aggregating multiple-discontinuous-image saliency prediction with transformer-based attention. In: 2022 International Conference on Robotics and Automation (ICRA). pp. 6571–6577. IEEE (2022)
2022
Later among the works it cites.
Lin, A., Chen, B., Xu, J., Zhang, Z., Lu, G., Zhang, D.: Ds-transunet: Dual swin transformer u-net for medical image segmentation. IEEE Transactions on Instrumentation and Measurement 71
2022
Later among the works it cites.
Ma, C., Sun, H., Rao, Y., Zhou, J., Lu, J.: Video saliency forecasting transformer. IEEE Transactions on Circuits and Systems for Video Technology 32
2022
Later among the works it cites.
Natan, O., Miura, J.: End-to-end autonomous driving with semantic depth cloud mapping and multi-agent. IEEE Transactions on Intelligent Vehicles 8
2022
Later among the works it cites.
2022
Later among the works it cites.
Shao, H., Wang, L., Chen, R., Li, H., Liu, Y.: Safety-enhanced autonomous driving using interpretable sensor fusion transformer. In: Conference on Robot Learning. pp. 726–737. PMLR (2022)
2022
Later among the works it cites.
Tian, H., Deng, T., Yan, H.: Driving as well as on a sunny day? predicting driver’s fixation in rainy weather conditions via a dual-branch visual model. IEEE/CAA Journal of Automatica Sinica 9
2022
Later among the works it cites.
Wu, P., Jia, X., Chen, L., Yan, J., Li, H., Qiao, Y.: Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline. Advances in Neural Information Processing Systems 35
2022
Later among the works it cites.
Xie, C., Xia, C., Ma, M., Zhao, Z., Chen, X., Li, J.: Pyramid grafting network for one-stage high resolution saliency detection. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 11717–11726 (2022)
2022
Later among the works it cites.
Chen, Y., Nan, Z., Xiang, T.: Fblnet: Feedback loop network for driver attention prediction. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 13371–13380 (2023)
2023
Later among the works it cites.
Deng, T., Jiang, L., Shi, Y., Wu, J., Wu, Z., Yan, S., Zhang, X., Yan, H.: Driving visual saliency prediction of dynamic night scenes via a spatio-temporal dual-encoder network. IEEE Transactions on Intelligent Transportation Systems (2023)
2023
Later among the works it cites.
Fu, R., Huang, T., Li, M., Sun, Q., Chen, Y.: A multimodal deep neural network for prediction of the driver’s focus of attention based on anthropomorphic attention mechanism and prior knowledge. Expert Systems with Applications 214
2023
Later among the works it cites.
Hu, Y., Yang, J., Chen, L., Li, K., Sima, C., Zhu, X., Chai, S., Du, S., Lin, T., Wang, W., et al.: Planning-oriented autonomous driving. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 17853–17862 (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
Jia, X., Gao, Y., Chen, L., Yan, J., Liu, P.L., Li, H.: Driveadapter: Breaking the coupling barrier of perception and planning in end-to-end autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 7953–7963 (2023)
2023
Later among the works it cites.
Jia, X., Wu, P., Chen, L., Xie, J., He, C., Yan, J., Li, H.: Think twice before driving: Towards scalable decoders for end-to-end autonomous driving. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 21983–21994 (2023)
2023
Later among the works it cites.
Shao, H., Wang, L., Chen, R., Waslander, S.L., Li, H., Liu, Y.: Reasonnet: End-to-end driving with temporal and global reasoning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 13723–13733 (2023)
2023
Later among the works it cites.
Shi, Y., Zhao, S., Wu, J., Wu, Z., Yan, H.: Fixated object detection based on saliency prior in traffic scenes. IEEE Transactions on Circuits and Systems for Video Technology (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
Zhang, J., Huang, Z., Ohn-Bar, E.: Coaching a teachable student. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7805–7815 (2023)
2023
Later among the works it cites.