Teacher-Student Cross-Domain Object Detection Model Combining Style Transfer and Adversarial Learning
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8549-4_28
Reference27 articles.
1. Tong, J., Chen, T., Wang, Q., Yao, Y.: Few-shot object detection via understanding convolution and attention. In: Pattern Recognition and Computer Vision: 5th Chinese Conference, PRCV 2022, Shenzhen, China, 4–7 November 2022, Proceedings, Part I, pp. 674–687. Springer, Heidelberg (2022). https://doi.org/10.1007/978-3-031-18907-4_52
2. Zhou, K., Deng, K., Chen, P., Hu, Y.: An improved lightweight network based on MobileNetV3 for Palmprint recognition. In: Pattern Recognition and Computer Vision: 5th Chinese Conference, PRCV 2022, Shenzhen, China, 4–7 November 2022, Proceedings, Part I, pp. 749–761. Springer, Heidelberg (2022). https://doi.org/10.1007/978-3-031-18907-4_58
3. Gu, J., et al.: MSINet: twins contrastive search of multi-scale interaction for object ReID. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 19243–19253 (2023)
4. Jin, L., et al.: Rethinking the person localization for single-stage multi-person pose estimation. IEEE Trans. Multimedia (2023)
5. Michaelis, C., et al.: Benchmarking robustness in object detection: Autonomous driving when winter is coming. arXiv preprint arXiv:1907.07484 (2019)
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