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Video annotation is expensive and time consuming.
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Andriluka, M., Iqbal, U., Ensafutdinov, E., Pishchulin, L., Milan, A., Gall, J., B., S.: PoseTrack: A benchmark for human pose estimation and tracking. In: CVPR (2018)
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Chen, Y., Wang, Z., Peng, Y., Zhang, Z., Yu, G., Sun, J.: Cascaded pyramid network for multi-person pose estimation. In: CVPR (2018)
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2018
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Doering, A., Iqbal, U., Gall, J.: Joint flow: Temporal flow fields for multi person tracking. In: BMVC (2018)
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Girdhar, R., Gkioxari, G., Torresani, L., Paluri, M., Tran, D.: Detect-and-Track: Efficient Pose Estimation in Videos. In: CVPR (2018)
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Guo, H., Tang, T., Luo, G., Chen, R., Lu, Y., Wen, L.: Multi-domain pose network for multi-person pose estimation and tracking. In: CVPR (2018)
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Kocabas, M., Karagoz, S., Akbas, E.: MultiPoseNet: Fast multi-person pose estimation using pose residual network. In: ECCV (2018)
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Ruan, W., Liu, W., Bao, Q., Chen, J., Cheng, Y., Mei, T.: POINet: Pose-guided ovonic insight network for multi-person pose tracking. In: International Conference on Multimedia (2019)
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Wang, X., Jabri, A., Efros, A.A.: Learning correspondence from the cycle-consistency of time. In: CVPR (2019)
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Bao, Q., Liu, W., Cheng, Y., Zhou, B., Mei, T.: Pose-guided tracking-by-detection: Robust multi-person pose tracking. IEEE Transactions on Multimedia (2020)
2020
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