The past decade has witnessed a rapid proliferation of video cameras in all walks of life and
has resulted in a tremendous explosion of video content. Several applications such as …

We introduce HuMoR: a 3D Human Motion Model for Robust Estimation of temporal pose
and shape. Though substantial progress has been made in estimating 3D human motion …

Human motion prediction is a challenging task due to the stochasticity and aperiodicity of
future poses. Recently, graph convolutional network has been proven to be very effective to …

Human movement is goal-directed and influenced by the spatial layout of the objects in the
scene. To plan future human motion, it is crucial to perceive the environment–imagine how …

Abstract We propose the Encoder-Recurrent-Decoder (ERD) model for recognition and
prediction of human body pose in videos and motion capture. The ERD model is a recurrent …

Human motion modeling is a classic problem in com-puter vision and graphics. Challenges
in modeling human motion include high dimensional prediction as well as extremely …

Despite the great progress in human motion prediction, it remains a challenging task due to
the complicated structural dynamics of human behaviors. In this paper, we address this …

Predicting and understanding human motion dynamics has many applications, such as
motion synthesis, augmented reality, security, and autonomous vehicles. Due to the recent …

We explore an approach to forecasting human motion in a few milliseconds given an input
3D skeleton sequence based on a recurrent encoder-decoder framework. Current …

With the rapid expansion of new available information presented to us online on a daily
basis, text classification becomes imperative in order to classify and maintain it. Word2vec …