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Neural Kinematic Networks for Unsupervised Motion Retargetting
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Time Target Character 2 Input Motion Target Character 1 Figure 1: Our end-to-end method retargets a given input motion (top row), to new characters with different bone lengths and proportions, (middle and bottom row). The target characters are never seen performing the input motion during training. Abstract We propose a recurrent neural network architecture with a Forward Kinematics layer and cycle consistency based adversarial training objective for unsupervised motion retargetting. Our
doi:10.1109/cvpr.2018.00901
dblp:conf/cvpr/VillegasYCL18
fatcat:clvz2m7ssvfxrellhbfd2mfp5y