Multi-Level Features Cascade for Person Re-Identification Based on Attention Mechanism

Zhengyi Zhang; Jianwei Ding; Huiwen Wei; Xiaotong Xiao

doi:10.3788/LOP202158.2215003

[1] Zhu X B, Che J. Person re-identification algorithm based on feature fusion and subspace learning[J]. Laser & Optoelectronics Progress, 56, 021503(2019).

[2] Dalal N, Triggs B. Histograms of oriented gradients for human detection[C]. //2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), June 20-25, 2005, San Diego, CA, USA., 886-893(2005).

[3] Wu L, Shen C H, Hengel A. PersonNet: person re-identification with deep convolutional neural networks[EB/OL]. (2016-01-27)[2020-11-20]. https://arxiv.org/abs/1601.07255

[4] Zheng L, Zhang H H, Sun S Y et al. Person re-identification in the wild[C]. //2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA., 3346-3355(2017).

[5] Qian X L, Fu Y W, Jiang Y G et al. Multi-scale deep learning architectures for person re-identification[C]. //2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy., 5409-5418(2017).

[6] Zhang T, Yi Z M, Li X et al. Improved algorithm for person re-identification based on global features[J]. Laser & Optoelectronics Progress, 57, 241503(2020).

[7] Zhao L M, Li X, Zhuang Y T et al. Deeply-learned part-aligned representations for person re-identification[C]. //2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy., 3239-3248(2017).

[8] Suh Y, Wang J D, Tang S Y et al. Part-aligned bilinear representations for person re-identification[M]. //Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11218, 418-437(2018).

[9] Xu L Z, Peng L. Person reidentification based on multiscale convolutional feature fusion[J]. Laser & Optoelectronics Progress, 56, 141504(2019).

[10] Chen T L, Ding S J, Xie J Y et al. ABD-Net: attentive but diverse person re-identification[C]. //2019 IEEE/CVF International Conference on Computer Vision (ICCV), October 27-November 2, 2019, Seoul, Korea (South), 8350-8360(2019).

[11] Zhang H, Goodfellow I, Metaxas D et al. Self-attention generative adversarial networks[EB/OL]. (2018-05-21)[2020-11-20]. http://export.arxiv.org/abs/1805.08318

[12] Zheng L, Shen L Y, Tian L et al. Scalable person re-identification: a benchmark[C]. //2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile, 1116-1124(2015).

[13] Ristani E, Solera F, Zou R et al. Performance measures and a data set for multi-target, multi-camera tracking[M]. // Hua G, Jégou H. Computer vision-ECCV 2016. Lecture notes in computer science, 9914, 17-35(2016).

[14] Li W, Zhao R, Xiao T et al. DeepReID: deep filter pairing neural network for person re-identification[C]. //2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA, 152-159(2014).

[15] Zhong Z, Zheng L, Cao D L et al. Re-ranking person re-identification with k-reciprocal encoding[C]. //2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA., 3652-3661(2017).

[16] Sun Y F, Zheng L, Deng W J et al. SVDNet for pedestrian retrieval[C]. //2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy., 3820-3828(2017).

[17] Sun Y F, Zheng L, Yang Y et al. Beyond part models: person retrieval with refined part pooling (and a strong convolutional baseline)[M]. //Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11208, 501-518(2018).

[18] Wang Y, Wang L Q, You Y R et al. Resource aware person re-identification across multiple resolutions[C]. //2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA., 8042-8051(2018).

[19] Luo H, Jiang W, Zhang X et al. AlignedReID++: dynamically matching local information for person re-identification[J]. Pattern Recognition, 94, 53-61(2019).

[20] Zheng M, Karanam S, Wu Z Y et al. Re-identification with consistent attentive siamese networks[C]. //2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA., 5728-5737(2019).