Visual tempo characterizes the dynamics and the temporal evolution, which helps describe
actions. Recent approaches directly perform visual tempo prediction on skeleton sequences …

Existing knowledge distillation (KD) method normally fixes the weight of the teacher network,
and uses the knowledge from the teacher network to guide the training of the student …

Recognizing human actions in dark videos is a useful yet challenging visual task in reality.
Existing augmentation-based methods separate action recognition and dark enhancement …

Video action recognition is a fundamental task for video understanding. Action recognition in
complex spatio-temporal contexts generally requires fusing of different multi-granularity …

Currently, video behavior recognition is one of the most foundational tasks of computer
vision. The 2D neural networks of deep learning are built for recognizing pixel-level …

In recent days, research in human activity recognition (HAR) has played a significant role in
healthcare systems. The accurate activity classification results from the HAR enhance the …

Visual tempos show the dynamics of action instances, characterizing the diversity of the
actions, such as walking slowly and running quickly. To facilitate action recognition, it is …

Action Recognition is a fundamental task in computer vision field, with a wide range of
applications in autonomous driving, security monitoring, etc. However, previous action …

Semi-supervised learning for video action recognition is a very challenging research area.
Existing state-of-the-art methods perform data augmentation on the temporality of actions …

Recognizing human actions in video sequences, known as Human Action Recognition
(HAR), is a challenging task in pattern recognition. While Convolutional Neural Networks …