Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Deep learning algorithms are a subset of the machine learning algorithms, which aim at
discovering multiple levels of distributed representations. Recently, numerous deep learning …

We propose a new bottom-up method for multi-person 2D human pose estimation that is
particularly well suited for urban mobility such as self-driving cars and delivery robots. The …

Human pose estimation localizes body keypoints to accurately recognizing the postures of
individuals given an image. This step is a crucial prerequisite to multiple tasks of computer …

Human pose estimation has received significant attention recently due to its various
applications in the real world. As the performance of the state-of-the-art human pose …

For human pose estimation in monocular images, joint occlusions and overlapping upon
human bodies often result in deviated pose predictions. Under these circumstances, bi …

The objective of this work is human pose estimation in videos, where multiple frames are
available. We investigate a ConvNet architecture that is able to benefit from temporal context …

We propose a ConvNet model for predicting 2D human body poses in an image. The model
regresses a heatmap representation for each body keypoint, and is able to learn and …

In this paper, we propose a deep convolutional neural network for 3D human pose
estimation from monocular images. We train the network using two strategies:(1) a multi-task …

We present a method for estimating articulated human pose from a single static image
based on a graphical model with novel pairwise relations that make adaptive use of local …