Deep Adversarial Attention Alignment for Unsupervised Domain Adaptation: the Benefit of Target Expectation Maximization

LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proceedings of the IEEE 86

1998

Earlier work this paper cites.

Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. pp. 248–255. IEEE (2009)

2009

Earlier work this paper cites.

Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: Contour detection and hierarchical image segmentation. IEEE transactions on pattern analysis and machine intelligence 33

2011

Earlier work this paper cites.

Simonyan, K., Vedaldi, A., Zisserman, A.: Deep inside convolutional networks: Visualising image classification models and saliency maps. arXiv preprint arXiv:1312.6034 (2013)

Original

2013

Earlier work this paper cites.

Tzeng, E., Hoffman, J., Zhang, N., Saenko, K., Darrell, T.: Deep domain confusion: Maximizing for domain invariance. arXiv preprint arXiv:1412.3474 (2014)

Original

2014

Earlier work this paper cites.

Zeiler, M.D., Fergus, R.: Visualizing and understanding convolutional networks. In: European conference on computer vision. pp. 818–833. Springer (2014)

2014

Earlier work this paper cites.

Ding, M., Fan, G.: Multilayer joint gait-pose manifolds for human gait motion modeling. IEEE Trans. Cybernetics 45

2015

Earlier work this paper cites.

Ganin, Y., Lempitsky, V.: Unsupervised domain adaptation by backpropagation. In: International Conference on Machine Learning. pp. 1180–1189 (2015)

2015

Earlier work this paper cites.

Long, M., Cao, Y., Wang, J., Jordan, M.: Learning transferable features with deep adaptation networks. In: International Conference on Machine Learning. pp. 97–105 (2015)

2015

Earlier work this paper cites.

Tzeng, E., Hoffman, J., Darrell, T., Saenko, K.: Simultaneous deep transfer across domains and tasks. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 4068–4076 (2015)

2015

Earlier work this paper cites.

Bousmalis, K., Trigeorgis, G., Silberman, N., Krishnan, D., Erhan, D.: Domain separation networks. In: Advances in Neural Information Processing Systems. pp. 343–351 (2016)

2016

Earlier work this paper cites.

He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 770–778 (2016)

2016

Cited alongside, same era.

He, K., Zhang, X., Ren, S., Sun, J.: Identity mappings in deep residual networks. In: European Conference on Computer Vision. pp. 630–645. Springer (2016)

2016

Cited alongside, same era.

Liu, M.Y., Tuzel, O.: Coupled generative adversarial networks. In: Advances in neural information processing systems. pp. 469–477 (2016)

2016

Cited alongside, same era.

Luc, P., Couprie, C., Chintala, S., Verbeek, J.: Semantic segmentation using adversarial networks. In: NIPS Workshop on Adversarial Training (2016)

2016

Cited alongside, same era.

Sun, B., Saenko, K.: Deep coral: Correlation alignment for deep domain adaptation. In: Computer Vision–ECCV 2016 Workshops. pp. 443–450. Springer (2016)

Long, M., Wang, J., Jordan, M.I.: Deep transfer learning with joint adaptation networks. In: ICML (2017)

2017

Later among the works it cites.

Russo, P., Carlucci, F.M., Tommasi, T., Caputo, B.: From source to target and back: symmetric bi-directional adaptive gan. arXiv preprint arXiv:1705.08824 (2017)

Original

2017

Later among the works it cites.

Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-cam: Visual explanations from deep networks via gradient-based localization. In: ICCV. pp. 618–626 (2017)

2017

Later among the works it cites.

Shrivastava, A., Pfister, T., Tuzel, O., Susskind, J., Wang, W., Webb, R.: Learning from simulated and unsupervised images through adversarial training. In: CVPR (2017)

2017

Later among the works it cites.

Tzeng, E., Hoffman, J., Saenko, K., Darrell, T.: Adversarial discriminative domain adaptation. In: Computer Vision and Pattern Recognition (CVPR) (2017)