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Adversarial Refinement Network for Human Motion Prediction
[article]
2020
arXiv
pre-print
Human motion prediction aims to predict future 3D skeletal sequences by giving a limited human motion as inputs. Two popular methods, recurrent neural networks and feed-forward deep networks, are able to predict rough motion trend, but motion details such as limb movement may be lost. To predict more accurate future human motion, we propose an Adversarial Refinement Network (ARNet) following a simple yet effective coarse-to-fine mechanism with novel adversarial error augmentation. Specifically,
arXiv:2011.11221v2
fatcat:7w6quwsgd5c4rdy2echwm4wlcq