Effective Use of Synthetic Data for Urban Scene Semantic Segmentation

Author:

Saleh Fatemeh SadatORCID,Aliakbarian Mohammad SadeghORCID,Salzmann MathieuORCID,Petersson LarsORCID,Alvarez Jose M.ORCID

Publisher

Springer International Publishing

Reference53 articles.

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2. Lecture Notes in Computer Science;A Bearman,2016

3. Brostow, G.J., Fauqueur, J., Cipolla, R.: Semantic object classes in video: a high-definition ground truth database. Pattern Recognit. Lett. 30(2), 88–97 (2009)

4. Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. arXiv preprint arXiv:1606.00915 (2016)

5. Chen, Y.H., Chen, W.Y., Chen, Y.T., Tsai, B.C., Wang, Y.C.F., Sun, M.: No more discrimination: cross city adaptation of road scene segmenters. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 2011–2020. IEEE (2017)

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