Human from Blur: Human Pose Tracking from Blurry Images
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Author / Producer
Date
2023
Publication Type
Conference Paper
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yes
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Abstract
We propose a method to estimate 3D human poses from substantially blurred images. The key idea is to tackle the inverse problem of image deblurring by modeling the forward problem with a 3D human model, a texture map, and a sequence of poses to describe human motion. The blurring process is then modeled by a temporal image aggregation step. Using a differentiable renderer, we can solve the inverse problem by backpropagating the pixel-wise reprojection error to recover the best human motion representation that explains a single or multiple input images. Since the image reconstruction loss alone is insufficient, we present additional regularization terms. To the best of our knowledge, we present the first method to tackle this problem. Our method consistently outperforms other methods on significantly blurry inputs since they lack one or multiple key functionalities that our method unifies, i.e. image deblurring with sub-frame accuracy and explicit 3D modeling of non-rigid human motion.
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published
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Book title
2023 IEEE/CVF International Conference on Computer Vision (ICCV)
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Volume
Pages / Article No.
14859 - 14859
Publisher
IEEE
Event
19th IEEE/CVF International Conference on Computer Vision (ICCV 2023)
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Methods
Software
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Organisational unit
03766 - Pollefeys, Marc / Pollefeys, Marc
03979 - Hilliges, Otmar (ehemalig) / Hilliges, Otmar (former)
Notes
Conference lecture held on October 5, 2023.