Citation: | QIN Pinle, SHEN Wenxiang, ZENG Jianchao, “DSCA-Net: Indoor Head Detection Network Using Dual-Stream Information and Channel Attention,” Chinese Journal of Electronics, vol. 29, no. 6, pp. 1102-1109, 2020, doi: 10.1049/cje.2020.09.011 |
X. Wei, J. Du, M. Liang et al., "Crowd density field estimation based on crowd dynamics theory and social force model", Chinese Journal of Electronics, Vol. 28, No.3, pp.521-528, 2019.
|
J. Li, Y. Wang, C. Wang, et al., "DSFD:Dual shot face Detector", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA, pp.5055-5064, 2019.
|
M. Najibi, P. Samangouei, R. Chellappa, et al., "SSH:Single stage headless face detector", IEEE International Conference on Computer Vision (ICCV), Venice, pp.4885-4894, 2017.
|
S. Zhang, J. Yang and B. Schiele, "Occluded pedestrian detection through guided attention in cnns", IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, pp.6995-7003, 2018.
|
J. Mao, T. Xiao, Y. Jiang, et al., "What can help pedestrian detection?", 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, pp.6034-6043, 2017.
|
K. Zhang, Z. Zhang, Z. Li, et al., "Joint face detection and alignment using multitask cascaded convolutional networks", IEEE Signal Processing Letters, Vol.23, No.10, pp.1499-1503, 2016.
|
A. Neubeck and L. Van Gool, "Efficient non-maximum suppression", 18th International Conference on Pattern Recognition (ICPR' 06), Hong Kong, China, pp.850-855, 2006.
|
B. Singh and L. S. Davis, "An analysis of scale invariance in object detection", 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 2018.
|
W. Liu, D. Anguelov, D. Erhan, et al., "SSD:Single shot multibox detector", 14th European Conference, Amsterdam, The Netherlands, pp.21-37, 2016.
|
T. Lin, P. Dollar, R. Girshick, et al., "Feature pyramid networks for object detection", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, pp.936-944, 2017.
|
J. Hu, L. Shen and G. Sun, "Squeeze-and-excitation networks", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.42, No.8, pp.2011-2023, 2017.
|
X. Wang, R. Girshick, A. Gupta, et al., "Non-local neural networks", 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 2018.
|
A. Neubeck and L. Van Gool, "Efficient non-maximum suppression", 18th International Conference on Pattern Recognition (ICPR' 06), Hong Kong, China, pp.850-855, 2006.
|
S. Zhang, L. Wen, X. Bian, et al., "Single-shot renement neural network for object detection", 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, pp.4203-4212, 2018.
|
O. Vinyals, A. Toshev, S. Bengio, et al., "Show and tell:Lessons learned from the 2015 MSCOCO image captioning challenge", IEEE Transactions on Pattern Analysis & Machine Intelligence, Vol.39, No.4, pp.652-663, 2016.
|
T. Vu, A. Osokin and I. Laptev, "Context-aware CNNS for person head detection", International Conference on Computer Vision, ICCV 2015, Santiago, Chile, pp.2893-2901, 2015.
|
D. Peng, Z. Sun, Z. Chen, et al., "Detecting heads using feature refine net and cascaded multi-scale architecture", International Conference on Pattern Recognition(ICPR), Beijing, China, pp. 2528-2533, 2018.
|
Y. Zhang, D. Zhou, S. Chen, et al., "Single-image crowd counting via multi-column convolutional neural network", Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, pp.589-597, 2016.
|
D. B. Sam, S. Surya and R. V. Babu, "Switching convolutional neural network for crowd counting", Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, pp.4031-4039, 2017.
|
H. Fan and H. Ling, "Sanet:Structure-aware network for visual tracking", 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, HI, USA, pp.2217-2224, 2016.
|
F. Jiang, F. Guo and R. Ji, "Dsnet:Accelerate indoor scene semantic segmentation", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom, pp.3317-3321, 2019.
|