With the advent of technology, we are getting more comfortable with the use of gadgets,
cameras, etc., and find Artificial Intelligence as an integral part of most of the tasks we …

Action detection is an essential and challenging task, especially for densely labelled
datasets of untrimmed videos. The temporal relation is complex in those datasets, including …

In video understanding, most cross-modal knowledge distillation (KD) methods are tailored
for classification tasks, focusing on the discriminative representation of the trimmed videos …

Human activity recognition is one of the most studied topics in the field of computer vision. In
recent years, with the availability of RGB-D sensors and powerful deep learning techniques …

Handling long and complex temporal information is an important factor for action detection
tasks. This challenge is further aggravated by densely distributed actions in untrimmed …

Skeleton-based action segmentation requires recognizing composable actions in untrimmed
videos. Current approaches decouple this problem by first extracting local visual features …

In real-world scenarios, human actions often fall outside the distribution of training data,
making it crucial for models to recognize known actions and reject unknown ones. However …

Recognizing Activities of Daily Living (ADL) is a vital process for intelligent assistive robots,
but collecting large annotated datasets requires time-consuming temporal labeling and …

With an increasing number of elders living alone, care-giving from a distance becomes a
compelling need, particularly for safety. Real-time monitoring and action recognition are …

Abstract Vision-based Human Action Recognition (HAR) is a hot topic in computer vision.
Recently, deep-based HAR has shown promising results. HAR using a single data modality …