Pedestrian Attribute Recognition Algorithm Based on Multi-Scale Attention Network

Na Li; Yangyang Wu; Ying Liu; Jin Xing

doi:10.3788/LOP202158.0410025

[1] Schumann A, Stiefelhagen R. Person re-identification by deep learning attribute-complementary information[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), July 21-26, 2017, Honolulu, HI, USA., 1435-1443(2017).

[2] Su C, Yang F, Zhang S L et al. Multi-task learning with low rank attribute embedding for multi-camera person re-identification[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 1167-1181(2018).

[3] Schumann A, Specker A, Beyerer J. Attribute-based person retrieval and search in video sequences[C]∥2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), November 27-30, 2018, Auckland, New Ze, 1-6(2018).

[4] Deng Y B, Luo P, Loy C C et al. Pedestrian attribute recognition at far distance. [C]∥Proceedings of the 22nd ACM International Conference on Multimedia, November 3-7, 2014, Orlando, Florida, USA. New York: ACM, 789-792(2014).

[5] Gray D, Tao H. Viewpoint invariant pedestrian recognition with an ensemble of localized features[M]. ∥Forsyth D, Torr P, Zisserman A, et al. Computer Vision-ECCV 2018. Lecture Notes in Computer Science. Cham: Springer, 5302, 262-275(2018).

[6] Chen L L, Zhang Z D, Peng L. Real-time detection based on improved single shot MultiBox detector[J]. Laser & Optoelectronics Progress, 56, 011002(2019).

[7] Wang J Q, Li J S, Zhou X W et al. Improved SSD algorithm and its performance analysis of small target detection in remote sensing images[J]. Acta Optica Sinica, 39, 0628005(2019).

[8] Ou P, Zhang Z, Lu K et al. Object detectionin of remote sensing images based on convolutional neural networks[J]. Laser & Optoelectronics Progress, 56, 051002(2019).

[9] Li D W, Chen X T, Huang K Q. Multi-attribute learning for pedestrian attribute recognition in surveillance scenarios[C]∥2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), November 3-6, 2015, Kuala Lumpur, Malaysia., 111-115(2015).

[10] Sudowe P, Spitzer H, Leibe B. Person attribute recognition with a jointly-trained holistic CNN model[C]∥2015 IEEE International Conference on Computer Vision Workshop (ICCVW), December 7-13, 2015, Santiago, Chile., 329-337(2015).

[11] Park S, Zhu S C. Attributed grammars for joint estimation of human attributes, part and pose[C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile., 2372-2380(2015).

[12] Zhou Y, Yu K, Leng B et al[2020-09-15]. Weakly-supervised learning of mid-level features for pedestrian attribute recognition and localization [2020-09-15].http:∥arxiv., org/abs/1611, 05603. http://arxiv.org/abs/1611.05603

[13] Lin T Y, Dollár P, Girshick R et al. Feature pyramid networks for object detection[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA., 936-944(2017).

[14] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA., 770-778(2016).

[15] Hu J, Shen L, Albanie S et al[2020-09-11]. Squeeze-and-excitation networks [2020-09-11].https:∥arxiv., org/abs/1709, 01507.

[16] Li D W, Zhang Z, Chen X T et al[2020-09-15]. A richly annotated dataset for pedestrian attribute recognition [2020-09-15].https:∥arxiv., org/abs/1603, 07054.

[17] Saquib M S, Schumann A, Wang Y et al[2020-09-13]. Deep view-sensitive pedestrian attribute inference in an end-to-end model [2020-09-13].http:∥arxiv., org/abs/1707, 06089.

[18] Deng Y B, Luo P, Loy C C et al[2020-09-18]. Learning to recognize pedestrian attribute [2020-09-18].http:∥arxiv., org/abs/1501, 00901.

[19] Zhao X, Sang L F, Ding G G et al. Grouping attribute recognition for pedestrian with joint recurrent learning[C]∥Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, July 13-19, 2018, Stockholm,, 3177-3183(2018).

[20] Li D W, Chen X T, Zhang Z et al. Pose guided deep model for pedestrian attribute recognition in surveillance scenarios[C]∥2018 IEEE International Conference on Multimedia and Expo (ICME), July 23-27, 2018, San Diego, CA, USA., 1-6(2018).

[21] Liu X H, Zhao H Y, Tian M Q et al. HydraPlus-, 350-359(2017).

[22] Ji Z, He E L, Wang H R et al. Image-attribute reciprocally guided attention network for pedestrian attribute recognition[J]. Pattern Recognition Letters, 120, 89-95(2019). http://www.sciencedirect.com/science/article/pii/S016786551830727X