This paper tackles the problem of human motion prediction, consisting in forecasting future
body poses from historically observed sequences. State-of-the-art approaches provide good …

Our goal is to synthesize 3D human motions given textual inputs describing simultaneous
actions, for examplewaving hand'whilewalking'at the same time. We refer to generating such …

Generating 3D human motion based on textual descriptions has been a research focus in
recent years. It requires the generated motion to be diverse, natural, and conform to the …

Human motion prediction is a classical problem in computer vision and computer graphics,
which has a wide range of practical applications. Previous effects achieve great empirical …

Seizure events can manifest as transient disruptions in the control of movements which may
be organized in distinct behavioral sequences, accompanied or not by other observable …

In this work, we present MotionMixer, an efficient 3D human body pose forecasting model
based solely on multi-layer perceptrons (MLPs). MotionMixer learns the spatial-temporal 3D …

Generating vivid and diverse 3D co-speech gestures is crucial for various applications in
animating virtual avatars. While most existing methods can generate gestures from audio …

Human pose estimation in videos has wide-ranging practical applications across various
fields, many of which require fast inference on resource-scarce devices, necessitating the …

Predicting 3D human poses in real-world scenarios, also known as human pose forecasting,
is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and …

Stochastic human motion prediction aims to forecast multiple plausible future motions given
a single pose sequence from the past. Most previous works focus on designing elaborate …