This method can effectively re-edit human motion data without the need for data pre-processing steps such as segmentation, classification, and alignment.
The proposed method can process large data sets in parallel and automatically perform manifold learning without manual labelling and segmentation. In the final, ...
Duration: 3:15
Posted: Oct 17, 2016
Posted: Oct 17, 2016
Missing: automatic | Show results with:automatic
Human motion data editing based on a convolutional automatic encoder and manifold learning · D. ZhouXinzhu Feng +4 authors. Deyun Yang. Computer Science.
Nov 2, 2015 · We present a technique for learning a manifold of human motion data using Convolutional Autoencoders.
Missing: automatic | Show results with:automatic
We present a technique for learning a manifold of human motion data using Convolutional Autoencoders. Our approach is capable of learning a manifold on the ...
We present a technique for learning a manifold of human motion data using Convolutional Autoencoders. Our approach is capable of learning a manifold on the ...
Missing: editing | Show results with:editing
Human motion data editing based on a convolutional automatic encoder and manifold learning. Entertain. Comput. 30 (2019). [+][–]. Coauthor network. maximize.
We present a technique for learning a manifold of human motion data using Convolutional Autoencoders. Our approach is capable of learning a manifold on the ...
Missing: editing | Show results with:editing
The designed autoencoders provide a novel insight into the comparative performance of these an- imation representation methods in an analog architecture, ...