Avoid Orientation Confusion in Symmetrical Oriented Object Detection
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5678-0_21
Reference26 articles.
1. Yu, Y., Da, F.: Phase-shifting coder: predicting accurate orientation in oriented object detection. arXiv preprint arXiv:2211.06368 (2023)
2. Liu, Y., Gao, H., Guo, L., Qin, A., Cai, C., You, Z.: A data-flow oriented deep ensemble learning method for real-time surface defect inspection. IEEE Trans. Instrum. Meas. (2019). https://doi.org/10.1109/TIM.2019.2957849
3. Wu, H., Lei, R., Peng, Y.: PCBNet: a lightweight convolutional neural network for defect inspection in surface mount technology. IEEE Trans. Instrum. Meas. 71, 1–14 (2022). https://doi.org/10.1109/TIM.2022.3193183
4. Chen, Z., et al.: AutoAlign: pixel-instance feature aggregation for multi-modal 3D object detection. arXiv preprint arXiv:2201.06493 (2022)
5. Caesar, H., et al.: nuScenes: a multimodal dataset for autonomous driving. arXiv preprint arXiv:1903.11027 (2020)
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