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We present a novel dataset covering seasonal and challenging perceptual conditions for autonomous driving.
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Jung, E., Yang, N., Cremers, D.: Multi-frame GAN: Image enhancement for stereo visual odometry in low light. In: Conference on Robot Learning (CoRL). pp. 651–660 (2019)
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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: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 11621–11631 (2020)
2020
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Spencer, J., Bowden, R., Hadfield, S.: Same features, different day: Weakly supervised feature learning for seasonal invariance. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 6459–6468 (2020)
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von Stumberg, L., Wenzel, P., Khan, Q., Cremers, D.: GN-Net: The gauss-newton loss for multi-weather relocalization. IEEE Robotics and Automation Letters (RA-L) 5
2020
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