We have recently seen tremendous progress in realistic text-to-motion generation. Yet the
existing methods often fail or produce implausible motions with unseen text inputs which …

Abstract 3D pose transfer that aims to transfer the desired pose to a target mesh is one of the
most challenging 3D generation tasks. Previous attempts rely on well-defined parametric …

Capturing and preserving motion semantics is essential to motion retargeting between
animation characters. However most of the previous works neglect the semantic information …

Human hands, the primary means of non-verbal communication, convey intricate semantics
in various scenarios. Due to the high sensitivity of individuals to hand motions, even minor …

This paper introduces a novel deep-learning approach for human-to-robot motion
retargeting, enabling robots to mimic human poses accurately. Contrary to prior deep …

Motion mapping between characters with different structures but corresponding to
homeomorphic graphs, meanwhile preserving motion semantics and perceiving shape …

We present a novel data-driven framework for unsupervised human motion retargeting
which animates a target body shape with a source motion. This allows to retarget motions …

This paper introduces a novel approach for human-to-robot motion retargeting, enabling
robots to mimic human motion with precision while preserving the semantics of the motion …

Motion retargeting for animation characters has potential applications in fields such as
animation production and virtual reality. However, current methods either assume that the …

Creating believable motions for various characters has long been a goal in computer
graphics. Current learning-based motion synthesis methods depend on extensive motion …