Recent advances in data analytics and computer-aided diagnostics stimulate the vision of
patient-centric precision healthcare, where treatment plans are customized based on the …

Abstract We propose a Generative Adversarial Network (GAN) to forecast 3D human motion
given a sequence of past 3D skeleton poses. While recent GANs have shown promising …

Pedestrian motion trajectory prediction is an important task in intelligent driving, and it can
provide a valuable reference for the subsequent path decision of intelligent driving …

Human motion prediction from its historical poses is an essential task in computer vision; it is
successfully applied for human-machine interaction and intelligent driving. Recently …

We present a self-supervised approach with pose perceptual loss for automatic dance video
generation. Our method can produce a realistic dance video that conforms to the beats and …

Generating realistic character animations is of great importance in computer graphics and
related domains. Existing approaches for this application involve a significant amount of …

Statistical models of the human body surface are generally learned from thousands of high-
quality 3D scans in predefined poses to cover the wide variety of human body shapes and …

Learning visual similarity requires to learn relations, typically between triplets of images.
Albeit triplet approaches being powerful, their computational complexity mostly limits training …

Temporal alignment of fine-grained human actions in videos is important for numerous
applications in computer vision, robotics, and mixed reality. State-of-the-art methods directly …

Automated source separation algorithms have become a central tool in neuroengineering
and neuroscience, where they are used to decompose neurophysiological signal into its …