Human Pose Estimation (HPE) has received considerable attention during the past years,
improving its performance thanks to the use of Deep Learning, and introducing new …

Human pose estimation refers to the estimation of the location of body parts and how they
are connected in an image. Human pose estimation from monocular images has wide …

By taking the semantic object parsing task as an exemplar application scenario, we propose
the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of …

We describe a method for articulated human detection and human pose estimation in static
images based on a new representation of deformable part models. Rather than modeling …

In this work, we address the human parsing task with a novel Contextualized Convolutional
Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global …

Human pose estimation and semantic part segmentation are two complementary tasks in
computer vision. In this paper, we propose to solve the two tasks jointly for natural multi …

We consider inferring the future actions of people from a still image or a short video clip.
Predicting future actions before they are actually executed is a critical ingredient for enabling …

To understand human behaviors, action recognition based on videos is a common
approach. Compared with image-based action recognition, videos provide much more …

Semantic object parsing is a fundamental task for understanding objects in detail in
computer vision community, where incorporating multi-level contextual information is critical …

We present a novel approach to modeling human pose, together with interacting objects,
based on compositional models of local visual interactions and their relations. Skeleton …