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Novel-View Human Action Synthesis

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Computer Vision – ACCV 2020 (ACCV 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12625))

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Abstract

Novel-View Human Action Synthesis aims to synthesize the movement of a body from a virtual viewpoint, given a video from a real viewpoint. We present a novel 3D reasoning to synthesize the target viewpoint. We first estimate the 3D mesh of the target body and transfer the rough textures from the 2D images to the mesh. As this transfer may generate sparse textures on the mesh due to frame resolution or occlusions. We produce a semi-dense textured mesh by propagating the transferred textures both locally, within local geodesic neighborhoods, and globally, across symmetric semantic parts. Next, we introduce a context-based generator to learn how to correct and complete the residual appearance information. This allows the network to independently focus on learning the foreground and background synthesis tasks. We validate the proposed solution on the public NTU RGB+D dataset. The code and resources are available at https://bit.ly/36u3h4K.

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Notes

  1. 1.

    https://renderpeople.com/, accessed September 2020.

  2. 2.

    In practice, we manually annotate each of the \(N_f\) face into a unique body-part label.

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Acknowledgements

This project acknowledges the use of the ESPRC funded Tier 2 facility, JADE.

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Authors and Affiliations

  1. Centre for Intelligent Sensing, Queen Mary University of London, London, UK

    Mohamed Ilyes Lakhal & Andrea Cavallaro

  2. Technologies of Vision, Fondazione Bruno Kessler, Povo, Italy

    Davide Boscaini, Fabio Poiesi & Oswald Lanz

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  1. Mohamed Ilyes Lakhal
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  2. Davide Boscaini
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  3. Fabio Poiesi
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  4. Oswald Lanz
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  5. Andrea Cavallaro
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Correspondence to Mohamed Ilyes Lakhal .

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Editors and Affiliations

  1. Waseda University, Tokyo, Japan

    Hiroshi Ishikawa

  2. Institute of Automation of Chinese Academy of Sciences, Bei**g, China

    Cheng-Lin Liu

  3. Czech Technical University in Prague, Prague, Czech Republic

    Tomas Pajdla

  4. University of Pennsylvania, Philadelphia, PA, USA

    Jianbo Shi

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Lakhal, M.I., Boscaini, D., Poiesi, F., Lanz, O., Cavallaro, A. (2021). Novel-View Human Action Synthesis. In: Ishikawa, H., Liu, CL., Pajdla, T., Shi, J. (eds) Computer Vision – ACCV 2020. ACCV 2020. Lecture Notes in Computer Science(), vol 12625. Springer, Cham. https://doi.org/10.1007/978-3-030-69538-5_26

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