Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …

Accurate whole-body multi-person pose estimation and tracking is an important yet
challenging topic in computer vision. To capture the subtle actions of humans for complex …

We present PyMAF-X, a regression-based approach to recovering a parametric full-body
model from a single image. This task is very challenging since minor parametric deviation …

Fashion illustration is used by designers to communicate their vision and to bring the design
idea from conceptualization to realization, showing how clothes interact with the human …

Human pose estimation (HPE) has developed over the past decade into a vibrant field for
research with a variety of real-world applications like 3D reconstruction, virtual testing and re …

High-quality 3D human body reconstruction requires high-fidelity and large-scale training
data and appropriate network design that effectively exploits the high-resolution input …

In this work, we study the challenging problem of instance-aware human body part parsing.
We introduce a new bottom-up regime which achieves the task through learning category …

Edge-cloud collaborative video analytics is transforming the way data is being handled,
processed, and transmitted from the ever-growing number of surveillance cameras around …

The recent advancements in image-text diffusion models have stimulated research interest
in large-scale 3D generative models. Nevertheless, the limited availability of diverse 3D …

We propose an end-to-end trainable approach for multi-instance pose estimation, called
POET (POse Estimation Transformer). Combining a convolutional neural network with a …