[1] [1] Dalai N. and Triggs B., Histograms of Oriented Gradients for Human Detection, IEEE Computer Vision and Pattern Recognitio, 886 (2005).

[2] [2] Rabaud V. and Belongie S., Counting Crowded Moving Objects, IEEE Computer Vision and Pattern Recognition, 705 (2006).

[3] [3] Zhang Y., Zhou D., Chen S., Gao S. and Ma Y., Single- Image Crowd Counting via Multi-Column Convolutional Neural Network, IEEE Computer Vision and Pattern Recognition, 589 (2016).

[4] [4] Sam D. B., Surya S. and Babu R.V., Switching Convolutional Neural Network for Crowd Counting, IEEE Computer Vision and Pattern Recognition, 4031 (2017).

[5] [5] Cao X., Wang Z., Zhao Y. and Su F., Scale Aggregation Network for Accurate and Efficient Crowd Counting, European Conference on Computer Vision, 757 (2018).

[6] [6] Li Y., Zhang X. and Chen D., CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes, IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1091 (2018).

[7] [7] Idrees H., Soomro K. and Shah M., Detecting Humans in Dense Crowds Using Locally-Consistent Scale Prior and Global Occlusion Reasoning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986 (2015).

[8] [8] Arteta C., Lempitsky V. and Zisserman A., Counting in the Wild, European Conference on Computer Vision, 483 (2016).

[9] [9] Chen J., Su W. and Wang Z., Neurocomputing 382, 210 (2020).

[10] [10] Wang Q., Gao J., Lin W. and Li X., NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization, arXiv:2001.03360, 2020.

[11] [11] He K., Zhang X. and Ren S., Deep Residual Learning for Image Recognition, IEEE Conference on Computer Vision and Pattern Recognition, 770 (2016).

[12] [12] Zeng L., Xu X., Cai B., Qiu S. and Zhang T., Multi-Scale Convolutional Neural Networks for Crowd Counting, IEEE International Conference on Image Processing, 465 (2017).

[13] [13] Guo D., Li K., Zha Z. and Wang M., DadNet: Dilated- attention-Deformable Convnet for Crowd Counting, 27th ACM International Conference on Multimedia, 1823 (2019).

[14] [14] Jiang X., Xiao Z., Zhang B., Zhen X., Cao X., David D. and Shao L., Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks, IEEE Computer Vision and Pattern Recognition, 6126 (2019).

[15] [15] Gao J., Wang Q. and Li X., PCC Net: Perspective Crowd Counting via Spatial Convolutional Network, arXiv:1905.10085, 2019.

[16] [16] Sam D. B., Sajjan N. N. and Babu R. V., Divide and Grow: Capturing Huge Diversity in Crowd Images with Incrementally Growing CNN, IEEE Computer Vision and Pattern Recognition, 3618 (2018).

[17] [17] Liu C., Duan Y., Du J. and Xu T., IEEE Access 8, 48352 (2020).