Human-centric perceptions (eg, pose estimation, human parsing, pedestrian detection,
person re-identification, etc.) play a key role in industrial applications of visual models. While …

Human parsing aims to partition humans in image or video into multiple pixel-level semantic
parts. In the last decade, it has gained significantly increased interest in the computer vision …

Problems such as equipment defects or limited viewpoints will lead the captured point
clouds to be incomplete. Therefore, recovering the complete point clouds from the partial …

Human-centric perceptions include a variety of vision tasks, which have widespread
industrial applications, including surveillance, autonomous driving, and the metaverse. It is …

Gait recognition stands as one of the most pivotal remote identification technologies and
progressively expands across research and industry communities. However existing gait …

Generating realistic human 3D reconstructions using image or video data is essential for
various communication and entertainment applications. While existing methods achieved …

The studies of human clothing for digital avatars have predominantly relied on synthetic
datasets. While easy to collect synthetic data often fall short in realism and fail to capture …

Language-image pre-training is an effective technique for learning powerful representations
in general domains. However, when directly turning to person representation learning, these …

Human-centric perception tasks, eg, pedestrian detection, skeleton-based action
recognition, and pose estimation, have wide industrial applications, such as metaverse and …

Binary silhouettes and keypoint-based skeletons have dominated human gait recognition
studies for decades since they are easy to extract from video frames. Despite their success …