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Deep learning usually achieves the best results with complete supervision.
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Neuhold, G., Ollmann, T., Bulò, S.R., Kontschieder, P.: The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes. In: IEEE International Conference on Computer Vision (ICCV) (2017)
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Souly, N., Spampinato, C., Shah, M.: Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network. In: IEEE International Conference on Computer Vision (ICCV) (2017)
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Sun, C., Shrivastava, A., Singh, S., Gupta, A.: Revisiting Unreasonable Effectiveness of Data in Deep Learning Era. In: IEEE International Conference on Computer Vision (ICCV) (2017)
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Xie, S., Girshick, R., Dollár, P., Tu, Z., He, K.: Aggregated Residual Transformations for Deep Neural Networks. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)
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Zhao, H., Shi, J., Qi, X., Wang, X., Jia, J.: Pyramid Scene Parsing Network. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)
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Bilinski, P., Prisacariu, V.: Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
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Bulò, S.R., Porzi, L., Kontschieder, P.: In-Place Activated BatchNorm for Memory-Optimized Training of DNNs. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
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Chandra, S., Couprie, C., Kokkinos, I.: Deep Spatio-Temporal Random Fields for Efficient Video Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
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Chen, L.C., Collins, M.D., Zhu, Y., Papandreou, G., Zoph, B., Schroff, F., Adam, H., Shlens, J.: Searching for Efficient Multi-Scale Architectures for Dense Image Prediction. In: Conference on Neural Information Processing Systems (NeurIPS) (2018)
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Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. In: European Conference on Computer Vision (ECCV) (2018)
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Hoffman, J., Tzeng, E., Park, T., Zhu, J.Y., Isola, P., Saenko, K., Efros, A.A., Darrell, T.: CyCADA: Cycle-Consistent Adversarial Domain Adaptation. In: International Conference on Machine Learning (ICML) (2018)
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Huang, P.Y., Hsu, W.T., Chiu, C.Y., Wu, T.F., Sun, M.: Efficient Uncertainty Estimation for Semantic Segmentation in Videos. In: European Conference on Computer Vision (ECCV) (2018)
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Hung, W.C., Tsai, Y.H., Liou, Y.T., Lin, Y.Y., Yang, M.H.: Adversarial Learning for Semi-Supervised Semantic Segmentation. In: British Machine Vision Conference (BMVC) (2018)
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Ke, T.W., Hwang, J.J., Liu, Z., Yu, S.X.: Adaptive Affinity Fields for Semantic Segmentation. In: European Conference on Computer Vision (ECCV) (2018)
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Kong, S., Fowlkes, C.: Recurrent Scene Parsing with Perspective Understanding in the Loop. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
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Mahajan, D., Girshick, R., Ramanathan, V., He, K., Paluri, M., Li, Y., Bharambe, A., van der Maaten, L.: Exploring the Limits of Weakly Supervised Pretraining. In: European Conference on Computer Vision (ECCV) (2018)
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Tsai, Y.H., Hung, W.C., Schulter, S., Sohn, K., Yang, M.H., Chandraker, M.: Learning to Adapt Structured Output Space for Semantic Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
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Xie, J., Shuai, B., Hu, J.F., Lin, J., Zheng, W.S.: Improving Fast Segmentation With Teacher-student Learning. In: British Machine Vision Conference (BMVC) (2018)
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Yang, G., Zhao, H., Shi, J., Deng, Z., Jia, J.: SegStereo: Exploiting Semantic Information for Disparity Estimation. In: European Conference on Computer Vision (ECCV) (2018)
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Li, X., Zhang, L., You, A., Yang, M., Yang, K., Tong, Y.: Global Aggregation then Local Distribution in Fully Convolutional Networks. In: British Machine Vision Conference (BMVC) (2019)
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Li, Y., Yuan, L., Vasconcelos, N.: Bidirectional Learning for Domain Adaptation of Semantic Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
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Lian, Q., Lv, F., Duan, L., Gong, B.: Constructing Self-Motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach. In: IEEE International Conference on Computer Vision (ICCV) (2019)
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Liu, C., Chen, L.C., Schroff, F., Adam, H., Hua, W., Yuille, A., Fei-Fei, L.: Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
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Yang, M., Yu, K., Zhang, C., Li, Z., Yang, K.: DenseASPP for Semantic Segmentation in Street Scenes. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
2018
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Yu, C., Wang, J., Peng, C., Gao, C., Yu, G., Sang, N.: BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation. In: European Conference on Computer Vision (ECCV) (2018)
2018
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2018
Cited alongside, same era.
Zhang, H., Dana, K., Shi, J., Zhang, Z., Wang, X., Tyagi, A., Agrawal, A.: Context Encoding for Semantic Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
2018
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Zhao, H., Zhang, Y., Liu, S., Shi, J., Loy, C.C., Lin, D., Jia, J.: PSANet: Point-wise Spatial Attention Network for Scene Parsing. In: European Conference on Computer Vision (ECCV) (2018)
2018
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Zhu, X., Zhou, H., Yang, C., Shi, J., Lin, D.: Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation. In: European Conference on Computer Vision (ECCV) (2018)
2018
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Zou, Y., Yu, Z., Kumar, B.V.K.V., Wang, J.: Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training. In: European Conference on Computer Vision (ECCV) (2018)
2018
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Chen, Y., Li, W., Chen, X., Gool, L.V.: Learning Semantic Segmentation From Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
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Liu, Y., Shun, C., Wang, J., Shen, C.: Structured Knowledge Distillation for Dense Prediction. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
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Luo, Y., Liu, P., Guan, T., Yu, J., Yang, Y.: Significance-Aware Information Bottleneck for Domain Adaptive Semantic Segmentation. In: IEEE International Conference on Computer Vision (ICCV) (2019)
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Nekrasov, V., Chen, H., Shen, C., Reid, I.: Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
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2019
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Valada, A., Mohan, R., Burgard, W.: Self-Supervised Model Adaptation for Multimodal Semantic Segmentation. International Journal of Computer Vision (IJCV) (2019)
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Vu, T.H., Jain, H., Bucher, M., Cord, M., Perez, P.: ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
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2019
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
Yue, X., Zhang, Y., Zhao, S., Sangiovanni-Vincentelli, A., Keutzer, K., Gong, B.: Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization Without Accessing Target Domain Data. In: IEEE International Conference on Computer Vision (ICCV) (2019)
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Zhang, F., Chen, Y., Li, Z., Hong, Z., Liu, J., Ma, F., Han, J., Ding, E.: ACFNet: Attentional Class Feature Network for Semantic Segmentation. In: IEEE International Conference on Computer Vision (ICCV) (2019)
2019
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Zhang, L., Li, X., Arnab, A., Yang, K., Tong, Y., Torr, P.H.: Dual Graph Convolutional Network for Semantic Segmentation. In: British Machine Vision Conference (BMVC) (2019)
2019
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Zhang, Q., Zhang, J., Liu, W., Tao, D.: Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation. In: Conference on Neural Information Processing Systems (NeurIPS) (2019)
2019
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Zhang, Y., Qiu, Z., Liu, J., Yao, T., Liu, D., Mei, T.: Customizable Architecture Search for Semantic Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
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Zhu, Y., Sapra, K., Reda, F.A., Shih, K.J., Newsam, S., Tao, A., Catanzaro, B.: Improving Semantic Segmentation via Video Propagation and Label Relaxation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
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Zou, Y., Yu, Z., Liu, X., Kumar, B.V., Wang, J.: Confidence Regularized Self-Training. In: IEEE International Conference on Computer Vision (ICCV) (2019)
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Chang, W.L., Wang, H.P., Peng, W.H., Chiu, W.C.: Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
2020
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Li, Y., Song, L., Chen, Y., Li, Z., Zhang, X., Wang, X., Sun, J.: Learning Dynamic Routing for Semantic Segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
2020
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Wu, C.Y., Girshick, R., He, K., Feichtenhofer, C., Krähenbühl, P.: A Multigrid Method for Efficiently Training Video Models. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
2020
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