Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …

We present HOI4D, a large-scale 4D egocentric dataset with rich annotations, to catalyze the
research of category-level human-object interaction. HOI4D consists of 2.4 M RGB-D …

Point cloud videos exhibit irregularities and lack of order along the spatial dimension where
points emerge inconsistently across different frames. To capture the dynamics in point cloud …

Most existing point cloud upsampling methods have roughly three steps: feature extraction,
feature expansion and 3D coordinate prediction. However, they usually suffer from two …

Point cloud analysis (such as 3D segmentation and detection) is a challenging task,
because of not only the irregular geometries of many millions of unordered points, but also …

Abstract Today, state-of-the-art deep neural networks that process events first convert them
into dense, grid-like input representations before using an off-the-shelf network. However …

A key challenge for autonomous vehicles is to navigate in unseen dynamic environments.
Separating moving objects from static ones is essential for navigation, pose estimation, and …

Recent development of neural implicit function has shown tremendous success on high-
quality 3D shape reconstruction. However, most works divide the space into inside and …

Action recognition is a major branch of computer vision research. As a widely used
technology, action recognition has been applied to human–computer interaction, intelligent …