Given the prominence of 3D sensors in recent years, 3D point cloud scene data are worthy
to be further investigated. Point cloud scene understanding is a challenging task because of …

Abstract 3D reconstruction of human bodies remains an important research issue in
computer vision. It is a fundamental resource for many everyday applications, including in …

In human and hand pose estimation, heatmaps are a crucial intermediate representation for
a body or hand keypoint. Two popular methods to decode the heatmap into a final joint …

Recent advances in hand pose estimation have shed light on utilizing synthetic data to train
neural networks, which however inevitably hinders generalization to real-world data due to …

Direct mesh fitting for 3D hand shape reconstruction estimates highly accurate meshes.
However, the resulting meshes are prone to artifacts and do not appear as plausible hand …

Large-scale point cloud semantic segmentation is a critical aspect of environmental
information perception, with far-reaching applications in domains such as auto-driving …

Existing datasets for 3D hand-object interaction are limited either in the data cardinality, data
variations in interaction scenarios, or the quality of annotations. In this work, we present a …

Gesture recognition and its applications have been widely studied and received much
attention in recent years. Existing works on hand gesture recognition aim to train …

Pose estimation is remarkably successful under supervised learning, but obtaining
annotations, especially for new deployments, is costly and time-consuming. This work …

3D hand pose estimation from monocular RGB inputs is critical for augmented and virtual
reality applications, and has achieved remarkable progress due to the revolution of deep …