We introduce HoloPose, a method for holistic monocular 3D human body reconstruction. We
first introduce a part-based model for 3D model parameter regression that allows our …

We propose an end-to-end architecture for joint 2D and 3D human pose estimation in
natural images. Key to our approach is the generation and scoring of a number of pose …

Abstract 3D human body pose estimation and mesh recovery refer to the approximation of
body parts and joint locations and their recovery into a 3D model to visualize the …

Recovering 3D human body shape and pose from 2D images is a challenging task due to
high complexity and flexibility of human body, and relatively less 3D labeled data. Previous …

Recovery of articulated 3D structure from 2D observations is a challenging computer vision
problem with many applications. Current learning-based approaches achieve state-of-the …

3D landmark localization plays an important role in many aspects of 3D data processing,
from morphometric analysis to the initialization of mesh registration algorithms. In this work …

Recent advances in 3D human shape reconstruction from single images have shown
impressive results, leveraging on deep networks that model the so-called implicit function to …

In this work we address the problem of landmark localization in 3D point clouds by
extending the convolutional pose machine (CPM) architecture to facilitate landmark …

This paper concerns structured regression problems wherein the issue of covariate shift is
addressed, which aims at reducing the discrepancy in training and test data distributions …