Abstract 3D human pose estimation and mesh recovery have attracted widespread research
interest in many areas, such as computer vision, autonomous driving, and robotics. Deep …

Abstract 4D human perception plays an essential role in a myriad of applications, such as
home automation and metaverse avatar simulation. However, existing solutions which …

Abstract The 3D Human Pose Estimation (3D HPE) task uses 2D images or videos to predict
human joint coordinates in 3D space. Despite recent advancements in deep learning-based …

We address the challenge of content diversity and controllability in pedestrian simulation for
driving scenarios. Recent pedestrian animation frameworks have a significant limitation …

Simulation has emerged as an indispensable tool for scaling and accelerating the
development of self-driving systems. A critical aspect of this is simulating realistic and …

Training a 3D human keypoint detector from point clouds in a supervised manner requires
large volumes of high quality labels. While it is relatively easy to capture large amounts of …

Comprehensive capturing of human motions requires both accurate captures of complex
poses and precise localization of the human within scenes. Most of the HPE datasets and …

Depth estimation is usually ill-posed and ambiguous for monocular camera-based 3D multi-
person pose estimation. Since LiDAR can capture accurate depth information in long-range …

Autonomous driving is an exciting new industry, posing important research questions. Within
the perception module, 3D human pose estimation is an emerging technology, which can …

Accurate understanding and prediction of human behaviors are critical prerequisites for
autonomous vehicles, especially in highly dynamic and interactive scenarios such as …