2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IP-7.12
Paper Title LEARNING NONPARAMETRIC HUMAN MESH RECONSTRUCTION FROM A SINGLE IMAGE WITHOUT GROUND TRUTH MESHES
Authors Kevin Lin, Lijuan Wang, Ying Jin, Zicheng Liu, Microsoft, United States; Ming-Ting Sun, University of Washington, United States
SessionMLR-APPL-IP-7: Machine learning for image processing 7
LocationArea E
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Applications of Machine Learning: Machine Learning for 3D Image and Video Processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract We present a novel approach to learn human mesh reconstruction without ground truth mesh labels. This is made possible by introducing two new terms into the loss function of a graph convolutional neural network (Graph CNN). The first term is the Laplacian prior that acts as a regularizer on the mesh reconstruction. The second term is the part segmentation loss that forces the projected region of the reconstructed mesh to match the part segmentation. Extensive experiments validate the effectiveness of the proposed approach.