Lightweight Unsupervised Domain Adaptation by Convolutional Filter Reconstruction

Author:

Aljundi Rahaf,Tuytelaars Tinne

Publisher

Springer International Publishing

Reference18 articles.

1. Ganin, Y., Ustinova, E., Ajakan, H., Germain, P., Larochelle, H., Laviolette, F., Marchand, M., Lempitsky, V.: Domain-adversarial training of neural networks. J. Mach. Learn. Res. 17(59), 1–35 (2016)

2. Long, M., Wang, J.: Learning transferable features with deep adaptation networks. CoRR abs/1502.02791, 1, 2 (2015)

3. Fernando, B., Habrard, A., Sebban, M., Tuytelaars, T.: Unsupervised visual domain adaptation using subspace alignment. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2960–2967 (2013)

4. Gong, B., Grauman, K., Sha, F.: Connecting the dots with landmarks: discriminatively learning domain-invariant features for unsupervised domain adaptation. In: Proceedings of The 30th International Conference on Machine Learning, pp. 222–230 (2013)

5. Gopalan, R., Li, R., Chellappa, R.: Domain adaptation for object recognition: an unsupervised approach. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 999–1006. IEEE (2011)

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