GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation
Author:
Funder
University Grants Committee
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s11263-023-01869-9.pdf
Reference70 articles.
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2. Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A. & Zagoruyko, S. (2020). End-to-end object detection with transformers. In European conference on computer vision, pp 213–229.
3. Chen, X., Ma, H., Wan, J., Li, B. & Xia, T. (2017). Multi-view 3d object detection network for autonomous driving. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 1907–1915.
4. Choi, J., Chun, D., Kim, H. & Lee HJ. (2019). Gaussian yolov3: An accurate and fast object detector using localization uncertainty for autonomous driving. In proceedings of the IEEE international conference on computer vision, vol 2019-Oct, pp 02–511.
5. Delany, S. J., Segata, N., & Mac Namee, B. (2012). Profiling instances in noise reduction. Knowledge-Based Systems, 31, 28–40.
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