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 …

Though tremendous strides have been made in uncontrolled face detection, accurate and
efficient face localisation in the wild remains an open challenge. This paper presents a …

Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …

Recent years have seen remarkable advances in visual understanding. However, how to
understand a story-based long video with artistic styles, eg movie, remains challenging. In …

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

Cattle identification is crucial to be registered for breeding association, food quality tracing,
disease prevention and control and fake insurance claims. Traditional non-biometrics …

Detecting safety helmet wearing in surveillance videos is an essential task for safety
management, compliance with regulations, and reducing the death rate from construction …

Pedestrian detection is a crucial field of computer vision research which can be adopted in
various real-world applications (eg, self-driving systems). However, despite noticeable …

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

The detection algorithm commonly misses obscured pedestrians in traffic scenes with a high
pedestrian density because mutual occlusion among pedestrians reduces the prediction box …