Scene graph is a structured representation of a scene that can clearly express the objects,
attributes, and relationships between objects in the scene. As computer vision technology …

Visual representation learning is ubiquitous in various real-world applications, including
visual comprehension, video understanding, multi-modal analysis, human-computer …

In this paper, we propose ARCH (Animatable Reconstruction of Clothed Humans), a novel
end-to-end framework for accurate reconstruction of animation-ready 3D clothed humans …

We present DenseRaC, a novel end-to-end framework for jointly estimating 3D human pose
and body shape from a monocular RGB image. Our two-step framework takes the body pixel …

Advances in machine learning technology have enabled real-time extraction of semantic
information in signals which can revolutionize signal processing techniques and improve …

In this paper, we propose a pose grammar to tackle the problem of 3D human pose
estimation from a monocular RGB image. Our model takes estimated 2D pose as the input …

Semantic signal processing and communications are poised to play a central part in
developing the next generation of sensor devices and networks. A crucial component of a …

Aiming to understand how human (false-) belief—a core socio-cognitive ability—would affect
human interactions with robots, this paper proposes to adopt a graphical model to unify the …

Scene Graph Generation (SGG) aims to parse the image as a set of semantics, containing
objects and their relations. Currently, the SGG methods only stay at presenting the intuitive …

Scene graphs have proven to be highly effective for various scene understanding tasks due
to their compact and explicit representation of relational information. However, current …