Real-time in-between motion generation is universally required in games and highly
desirable in existing animation pipelines. Its core challenge lies in the need to satisfy three …

Recently, methods for skeleton-based human activity recognition have been shown to be
vulnerable to adversarial attacks. However, these attack methods require either the full …

Action recognition has been heavily employed in many applications such as autonomous
vehicles, surveillance, etc, where its robustness is a primary concern. In this paper, we …

Skeletal motion plays a vital role in human activity recognition as either an independent data
source or a complement. The robustness of skeleton-based activity recognizers has been …

With the rapid development of computing technology, three-dimensional (3D) human body
models and their dynamic motions are widely used in the digital entertainment industry …

We show that the task of synthesizing human motion conditioned on a set of key frames can
be solved more accurately and effectively if a deep learning based interpolator operates in …

We investigate a new task in human motion prediction which is predicting motions under
unexpected physical perturbation potentially involving multiple people. Compared with …

Close and continuous interaction with rich contacts is a crucial aspect of human activities (eg
hugging dancing) and of interest in many domains like activity recognition motion prediction …

Skeletal motions have been heavily relied upon for human activity recognition (HAR).
Recently, a universal vulnerability of skeleton-based HAR has been identified across a …

Styled online in-between motion generation has important application scenarios in computer
animation and games. Its core challenge lies in the need to satisfy four critical requirements …