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The crowd counting task aims at estimating the number of people located in an image or a frame from videos.
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Zhang, Y., Zhou, D., Chen, S., Gao, S., Ma, Y.: Single-image crowd counting via multi-column convolutional neural network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2016)
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Mao, J., Xiao, T., Jiang, Y., Cao, Z.: What can help pedestrian detection? In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017)
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Paul Cohen, J., Boucher, G., Glastonbury, C.A., Lo, H.Z., Bengio, Y.: Count-ception: Counting by fully convolutional redundant counting. In: Proceedings of the International Conference on Computer Vision (2017)
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Sindagi, V.A., Patel, V.M.: Generating high-quality crowd density maps using contextual pyramid CNNs. In: Proceedings of the International Conference on Computer Vision (2017)
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Babu Sam, D., Sajjan, N.N., Venkatesh Babu, R., Srinivasan, M.: Divide and Grow: Capturing huge diversity in crowd images with incrementally growing CNN. In: Proceedings of the IEEE conference on computer vision and pattern recognition (2018)
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Liu, W., Liao, S., Ren, W., Hu, W., Yu, Y.: High-level semantic feature detection: A new perspective for pedestrian detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2019)
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Ma, Z., Wei, X., Hong, X., Gong, Y.: Bayesian loss for crowd count estimation with point supervision. In: Proceedings of the International Conference on Computer Vision (2019)
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Shi, M., Yang, Z., Xu, C., Chen, Q.: Revisiting perspective information for efficient crowd counting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2019)
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Sindagi, V.A., Patel, V.M.: HA-CNN: Hierarchical attention-based crowd counting network. IEEE Transactions on Image Processing 29
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Cao, X., Wang, Z., Zhao, Y., Su, F.: Scale aggregation network for accurate and efficient crowd counting. In: Proceedings of the Europeon Conference on Computer Vision (2018)
2018
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Idrees, H., Tayyab, M., Athrey, K., Zhang, D., Al-Maadeed, S., Rajpoot, N., Shah, M.: Composition loss for counting, density map estimation and localization in dense crowds. In: Proceedings of the Europeon Conference on Computer Vision (2018)
2018
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Li, Y., Zhang, X., Chen, D.: CSRNet: Dilated convolutional neural networks for understanding the highly congested scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2018)
2018
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Sam, D.B., Babu, R.V.: Top-down feedback for crowd counting convolutional neural network. In: Thirty-second AAAI conference on artificial intelligence (2018)
2018
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Stahl, T., Pintea, S.L., van Gemert, J.C.: Divide and count: Generic object counting by image divisions. IEEE Transactions on Image Processing 28
2018
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Cheng, Z.Q., Li, J.X., Dai, Q., Wu, X., Hauptmann, A.G.: Learning spatial awareness to improve crowd counting. In: Proceedings of the International Conference on Computer Vision (2019)
2019
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Jiang, X., Xiao, Z., Zhang, B., Zhen, X., Cao, X., Doermann, D., Shao, L.: Crowd counting and density estimation by trellis encoder-decoder networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2019)
2019
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Liu, L., Qiu, Z., Li, G., Liu, S., Ouyang, W., Lin, L.: Crowd counting with deep structured scale integration network. In: Proceedings of the IEEE International Conference on Computer Vision (2019)
2019
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Sindagi, V.A., Patel, V.M.: Multi-level bottom-top and top-bottom feature fusion for crowd counting. In: Proceedings of the IEEE International Conference on Computer Vision (2019)
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Tian, Y., Lei, Y., Zhang, J., Wang, J.Z.: PaDNet: Pan-density crowd counting. IEEE Transactions on Image Processing (2019), DOI: 10.1109/TIP.2019.2952083
2019
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Wan, J., Chan, A.: Adaptive density map generation for crowd counting. In: Proceedings of the International Conference on Computer Vision (2019)
2019
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Wang, Q., Gao, J., Lin, W., Yuan, Y.: Learning from synthetic data for crowd counting in the wild. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2019)
2019
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Xiong, H., Lu, H., Liu, C., Liu, L., Cao, Z., Shen, C.: From open set to closed set: Counting objects by spatial divide-and-conquer. In: Proceedings of the International Conference on Computer Vision (2019)
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Xu, C., Qiu, K., Fu, J., Bai, S., Xu, Y., Bai, X.: Learn to scale: Generating multipolar normalized density maps for crowd counting. In: Proceedings of the International Conference on Computer Vision (2019)
2019
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Zhang, A., Shen, J., Xiao, Z., Zhu, F., Zhen, X., Cao, X., Shao, L.: Relational attention network for crowd counting. In: Proceedings of the IEEE International Conference on Computer Vision (2019)
2019
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