  We present a method to combine markerless motion capture and dense pose
feature estimation into a single framework. We demonstrate that dense pose
information can help for multiview/single-view motion capture, and multiview
motion capture can help the collection of a high-quality dataset for training
the dense pose detector. Specifically, we first introduce a novel markerless
motion capture method that can take advantage of dense parsing capability
provided by the dense pose detector. Thanks to the introduced dense human
parsing ability, our method is demonstrated much more efficient, and accurate
compared with the available state-of-the-art markerless motion capture
approach. Second, we improve the performance of available dense pose detector
by using multiview markerless motion capture data. Such dataset is beneficial
to dense pose training because they are more dense and accurate and consistent,
and can compensate for the corner cases such as unusual viewpoints. We
quantitatively demonstrate the improved performance of our dense pose detector
over the available DensePose. Our dense pose dataset and detector will be made
public.
