Compressing Human Body Video with Interactive Semantics: A Generative Approach
Journal:
arXiv
Published Date:
May 22, 2025
Abstract
In this paper, we propose to compress human body video with interactive
semantics, which can facilitate video coding to be interactive and controllable
by manipulating semantic-level representations embedded in the coded bitstream.
In particular, the proposed encoder employs a 3D human model to disentangle
nonlinear dynamics and complex motion of human body signal into a series of
configurable embeddings, which are controllably edited, compactly compressed,
and efficiently transmitted. Moreover, the proposed decoder can evolve the
mesh-based motion fields from these decoded semantics to realize the
high-quality human body video reconstruction. Experimental results illustrate
that the proposed framework can achieve promising compression performance for
human body videos at ultra-low bitrate ranges compared with the
state-of-the-art video coding standard Versatile Video Coding (VVC) and the
latest generative compression schemes. Furthermore, the proposed framework
enables interactive human body video coding without any additional
pre-/post-manipulation processes, which is expected to shed light on
metaverse-related digital human communication in the future.
