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In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.
Histograms of Oriented Gradients for Human Detection
Dalal, N., Triggs, B.: · 2005
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Pictorial Structures Revisited: People Detection and Articulated Pose Estimation
Andriluka, M., Roth, S., Schiele, B.: · 2009
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ImageNet: A Large-Scale Hierarchical Image Database
Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: · 2009
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Curriculum learning
Bengio, Y., Louradour, J., Collobert, R., Weston, J.: · 2009
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Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation
Johnson, S., Everingham, M.: · 2010
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Poselet conditioned pictorial structures
Pishchulin, L., Andriluka, M., Gehler, P., Schiele, B.: · 2013
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Articulated pose estimation with flexible mixtures-of-parts
Yang, Y., Ramanan, D.: · 2013
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Human Pose Estimation Using Body Parts Dependent Joint Regressors
Dantone, M., Gall, J., Leistner, C., Van Gool, L.: · 2013
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Human Pose Estimation Using a Joint Pixel-wise and Part-wise Formulation
Ladicky, L., Torr, P.H., Zisserman, A.: · 2013
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Articulated pose estimation using discriminative armlet classifiers
Gkioxari, G., Arbelaez, P., Bourdev, L., Malik, J.: · 2013
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Microsoft COCO: Common objects in context
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: · 2014
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Using k-poselets for detecting people and localizing their keypoints
Gkioxari, G., Hariharan, B., Girshick, R., Malik, J.: · 2014
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DeepPose: Human Pose Estimation via Deep Neural Networks
Toshev, A., Szegedy, C.: · 2014
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Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
Tompson, J., Jain, A., LeCun, Y., Bregler, C.: · 2014
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Pose machines: Articulated pose estimation via inference machines
Ramakrishna, V., Munoz, D., Hebert, M., Bagnell, A.J., Sheikh, Y.: · 2014
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Fast R-CNN
Girshick, R.: · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Ren, S., He, K., Girshick, R., Sun, J.: · 2015
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TensorFlow: Large-scale machine learning on heterogeneous systems (2015) Software available from tensorflow.org
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X.: · 2015
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Adam: A method for stochastic optimization
Kingma, D.P., Ba, J.: · 2015
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The pascal visual object classes challenge: A retrospective
Everingham, M., Eslami, S.M.A., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: · 2015
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DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
Pishchulin, L., Insafutdinov, E., Tang, S., Andres, B., Andriluka, M., Gehler, P., Schiele, B.: · 2016
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Deepercut: A deeper, stronger, and faster multi-person pose estimation model
Insafutdinov, E., Pishchulin, L., Andres, B., Andriluka, M., Schiele, B.: · 2016
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Human pose estimation via convolutional part heatmap regression
Bulat, A., Tzimiropoulos, G.: · 2016
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Multi-person pose estimation with local joint-to-person associations
Iqbal, U., Gall, J.: · 2016
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Convolutional Pose Machines
Wei, S.E., Ramakrishna, V., Kanade, T., Sheikh, Y.: · 2016
Towards Accurate Multi-person Pose Estimation in the Wild
Papandreou, G., Zhu, T., Kanazawa, N., Toshev, A., Tompson, J., Bregler, C., Murphy, K.: · 2017
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Mask R-CNN
He, K., Gkioxari, G., Dollár, P., Girshick, R.: · 2017
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RMPE: Regional Multi-Person Pose Estimation
Fang, H., Xie, S., Tai, Y., Lu, C.: · 2017
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Self Adversarial Training for Human Pose Estimation
Chou, C.J., Chien, J.T., Chen, H.T.: · 2017
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A Coarse-Fine Network for Keypoint Localization
Huang, S., Gong, M., Tao, D.: · 2017
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Multi-Context Attention for Human Pose Estimation
Chu, X., Yang, W., Ouyang, W., Ma, C., Yuille, A.L., Wang, X.: · 2017
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Stacked Hourglass Networks for Human Pose Estimation
Newell, A., Yang, K., Deng, J.: · 2016
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Human Pose Estimation with Iterative Error Feedback
Carreira, J., Agrawal, P., Fragkiadaki, K., Malik, J.: · 2016
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Human Pose Estimation using Deep Consensus Voting
Lifshitz, I., Fetaya, E., Ullman, S.: · 2016
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Rethinking the inception architecture for computer vision
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: · 2016
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Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., Sun, J.: · 2016
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Hypernet: Towards accurate region proposal generation and joint object detection
Kong, T., Yao, A., Chen, Y., Sun, F.: · 2016
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Recurrent Human Pose Estimation
Belagiannis, V., Zisserman, A.: · 2017
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A Greedy Part Assignment Algorithm for Realtime Multi-Person 2D Pose Estimation
Varadarajan, S., Datta, P., Tickoo, O.: · 2017
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PoseTrack: Joint Multi-Person Pose Estimation and Tracking
Iqbal, U., Milan, A., Gall, J.: · 2017
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DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: · 2017
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Joint Multi-Person Pose Estimation and Semantic Part Segmentation in a Single Image
Xia, F., Wang, P., Yuille, A., Angeles, L.: · 2017
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Feature Pyramid Networks for Object Detection
Lin, T.Y., Dollár, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: · 2017
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Focal loss for dense object detection
Lin, T.Y., Goyal, P., Girshick, R., He, K., Dollár, P.: · 2017
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Benchmarking and Error Diagnosis in Multi-Instance Pose Estimation
Ronchi, M.R., Perona, P.: · 2017
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Aggregated residual transformations for deep neural networks
Xie, S., Girshick, R., Dollár, P., Tu, Z., He, K.: · 2017
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Bayesian segnet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding
Kendall, A., Badrinarayanan, V., , Cipolla, R.: · 2017
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fizyr/keras-retinanet 0.2
Gaiser, H., de Vries, M., Williamson, A., Henon, Y., Morariu, M., Lacatusu, V., Liscio, E., Fang, W., Clark, M., Sande, M.V., Kocabas, M.: · 2018
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