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Person re-identification (re-ID), which aims to re-identify people across different camera views, has been significantly advanced by deep learning in recent years, particularly with convolutional neural networks (CNNs).
Chen, Y., , Han, C., Li, Y., Huang, Z., Jiang, Y., Wang, N., and Zhang, Z. (2019c) · 1903
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MMDetection: Open mmlab detection toolbox and benchmark
Chen, K., Wang, J., Pang, J., Cao, Y., Xiong, Y., Li, X., Sun, S., Feng, W., Liu, Z., Xu, J., Zhang, Z., Cheng, D., Zhu, C., Cheng, T., Zhao, Q., Li, B., Lu, X., Zhu, R., Wu, Y., Dai, J., Wang, J., Shi, J., Ouyang, W., Loy, C. C., and Lin, D. (2019b) · 1906
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On the variance of the adaptive learning rate and beyond
Liu, L., Jiang, H., He, P., Chen, W., Liu, X., Gao, J., and Han, J. (2019) · 1908
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Learning generalisable omni-scale representations for person re-identification
Zhou, K., Yang, Y., Cavallaro, A., and Xiang, T. (2019a) · 1910
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Evaluating appearance models for recognition, reacquisition, and tracking
Gray, D., Brennan, S., and Tao, H. (2007) · 2007
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L. (2009) · 2009
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Multi-camera activity correlation analysis
Loy, C. C., Xiang, T., and Gong, S. (2009) · 2009
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Associating groups of people
Zheng, W.-S., Gong, S., and Xiang, T. (2009) · 2009
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Human reidentification with transferred metric learning
Li, W., Zhao, R., and Wang, X. (2012) · 2012
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Locally aligned feature transforms across views
Li, W. and Wang, X. (2013) · 2013
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Caffe: Convolutional architecture for fast feature embedding
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., and Darrell, T. (2014) · 2014
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Adam: A method for stochastic optimization
Kingma, D. and Ba, J. (2014) · 2014
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Deepreid: Deep filter pairing neural network for person re-identification
Li, W., Zhao, R., Xiao, T., and Wang, X. (2014) · 2014
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Dropout: A simple way to prevent neural networks from overfitting
Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., and Salakhutdinov, R. (2014) · 2014
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Person re-identification by video ranking
Wang, T., Gong, S., Zhu, X., and Wang, S. (2014) · 2014
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An improved deep learning architecture for person re-identification
Ahmed, E., Jones, M., and Marks, T. K. (2015) · 2015
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Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems
Chen, T., Li, M., Li, Y., Lin, M., Wang, N., Wang, M., Xiao, T., Xu, B., Zhang, C., and Zhang, Z. (2015) · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, S. and Szegedy, C. (2015) · 2015
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Person re-identification by local maximal occurrence representation and metric learning
Liao, S., Hu, Y., Zhu, X., and Li, S. Z. (2015) · 2015
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Scalable person re-identification: A benchmark
Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., and Tian, Q. (2015) · 2015
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., et al. (2016) · 2016
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Deep transfer learning for person re-identification
Geng, M., Wang, Y., Xiang, T., and Tian, Y. (2016) · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J. (2016) · 2016
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Squeezenet: Alexnet-level accuracy with 50x fewer parameters and< 0.5 mb model size
Iandola, F. N., Han, S., Moskewicz, M. W., Ashraf, K., Dally, W. J., and Keutzer, K. (2016) · 2016
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Hierarchical gaussian descriptor for person re-identification
Matsukawa, T., Okabe, T., Suzuki, E., and Sato, Y. (2016) · 2016
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Performance measures and a data set for multi-target, multi-camera tracking
Ristani, E., Solera, F., Zou, R., Cucchiara, R., and Tomasi, C. (2016) · 2016
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Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer
Zagoruyko, S. and Komodakis, N. (2017) · 2017
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Spindle net: Person re-identification with human body region guided feature decomposition and fusion
Zhao, H., Tian, M., Sun, S., Shao, J., Yan, J., Yi, S., Wang, X., and Tang, X. (2017) · 2017
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Unlabeled samples generated by gan improve the person re-identification baseline in vitro
Zheng, Z., Zheng, L., and Yang, Y. (2017) · 2017
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Multi-level factorisation net for person re-identification
Chang, X., Hospedales, T. M., and Xiang, T. (2018) · 2018
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Allennlp: A deep semantic natural language processing platform
Gardner, M., Grus, J., Neumann, M., Tafjord, O., Dasigi, P., Liu, N., Peters, M., Schmitz, M., and Zettlemoyer, L. (2018) · 2018
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Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., and Wojna, Z. (2016) · 2016
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Learning deep feature representations with domain guided dropout for person re-identification
Xiao, T., Li, H., Ouyang, W., and Wang, X. (2016) · 2016
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Learning a discriminative null space for person re-identification
Zhang, L., Xiang, T., and Gong, S. (2016) · 2016
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Mars: A video benchmark for large-scale person re-identification
Zheng, L., Bie, Z., Sun, Y., Wang, J., Su, C., Wang, S., and Tian, Q. (2016) · 2016
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Xception: Deep learning with depthwise separable convolutions
Chollet, F. (2017) · 2017
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In defense of the triplet loss for person re-identification
Hermans, A., Beyer, L., and Leibe, B. (2017) · 2017
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Densely connected convolutional networks
Huang, G., Liu, Z., Weinberger, K. Q., and van der Maaten, L. (2017) · 2017
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Detectron
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Squeeze-and-excitation networks
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Harmonious attention network for person re-identification
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Shufflenet v2: Practical guidelines for efficient cnn architecture design
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Mobilenetv2: Inverted residuals and linear bottlenecks
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Beyond part models: Person retrieval with refined part pooling (and a strong convolutional baseline)
Sun, Y., Zheng, L., Yang, Y., Tian, Q., and Wang, S. (2018) · 2018
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Person transfer gan to bridge domain gap for person re-identification
Wei, L., Zhang, S., Gao, W., and Tian, Q. (2018) · 2018
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Exploit the unknown gradually: One-shot video-based person re-identification by stepwise learning
Wu, Y., Lin, Y., Dong, X., Yan, Y., Ouyang, W., and Yang, Y. (2018) · 2018
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Shufflenet: An extremely efficient convolutional neural network for mobile devices
Zhang, X., Zhou, X., Lin, M., and Sun, J. (2018) · 2018
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Learning transferable architectures for scalable image recognition
Zoph, B., Vasudevan, V., Shlens, J., and Le, Q. V. (2018) · 2018
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Torchmeta: A Meta-Learning library for PyTorch
Deleu, T., Würfl, T., Samiei, M., Cohen, J. P., and Bengio, Y. (2019) · 2019
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Interaction-and-aggregation network for person re-identification
Hou, R., Ma, B., Chang, H., Gu, X., Shan, S., and Chen, X. (2019) · 2019
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Huggingface’s transformers: State-of-the-art natural language processing
Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., and Brew, J. (2019) · 2019
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