Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand
pose estimation from single depth images. In this paper, we present an approach that …

We propose a unified formulation for the problem of 3D human pose estimation from a single
raw RGB image that reasons jointly about 2D joint estimation and 3D pose reconstruction to …

We present a bundle-adjustment-based algorithm for recovering accurate 3D human pose
and meshes from monocular videos. Unlike previous algorithms which operate on single …

Recovering human pose from RGB images and videos has drawn increasing attention in
recent years owing to minimum sensor requirements and applicability in diverse fields such …

Synthetic visual data can provide practicically infinite diversity and rich labels, while
avoiding ethical issues with privacy and bias. However, for many tasks, current models …

We propose a new 3D holistic++ scene understanding problem, which jointly tackles two
tasks from a single-view image:(i) holistic scene parsing and reconstruction---3D estimations …

In this paper, a feature boosting network is proposed for estimating 3D hand pose and 3D
body pose from a single RGB image. In this method, the features learned by the …

Event camera is an emerging imaging sensor for capturing dynamics of moving objects as
events, which motivates our work in estimating 3D human pose and shape from the event …

Vision not only detects and recognizes objects, but performs rich inferences about the
underlying scene structure that causes the patterns of light we see. Inverting generative …

We present a novel end-to-end framework named as GSNet (G eometric and S cene-aware
Net work), which jointly estimates 6DoF poses and reconstructs detailed 3D car shapes from …