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Titlebook: Articulated Motion and Deformable Objects; 10th International C Francisco José Perales,Josef Kittler Conference proceedings 2018 Springer I

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Sweta Raian-Rankin,Mark Tomlinson used to enhance the training of the autoencoder. The system has been evaluated in two standard datasets, HumanEva-I and Human3.6M, comprising more than 15 different activities. We show that our simple architecture can provide state of the art results.
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elligent vehicles or deep learning, to date no survey on multimodal deep learning for advanced driving exists. This paper attempts to narrow this gap by providing the first review that analyzes existing literature and two indispensable elements: sensors and datasets. We also provide our insights on future challenges and work to be done.
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Refining the Pose: Training and Use of Deep Recurrent Autoencoders for Improving Human Pose Estimat used to enhance the training of the autoencoder. The system has been evaluated in two standard datasets, HumanEva-I and Human3.6M, comprising more than 15 different activities. We show that our simple architecture can provide state of the art results.
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