Hierarchical contrastive adaptation for cross-domain object detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://link.springer.com/content/pdf/10.1007/s00138-022-01317-7.pdf
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3. Benenson, R., Popov, S., Ferrari, V.: Large-scale interactive object segmentation with human annotators. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) pp. 11692–11701 (2019)
4. Bousmalis, K., Silberman, N., Dohan, D., Erhan, D., Krishnan, D.: Unsupervised pixel-level domain adaptation with generative adversarial networks. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 95–104 (2017)
5. Cai, Q., Pan, Y., Ngo, C., Tian, X., Duan, L., Yao, T.: Exploring object relation in mean teacher for cross-domain detection. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) pp. 11449–11458 (2019)
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