Hashing has become increasingly popular in approximate nearest neighbor search in recent
years due to its storage and computational efficiency. While deep unsupervised hashing has …

Sketches reflect the drawing style of individual artists; therefore, it is important to consider
their unique styles when extracting sketches from color images for various applications …

Recently, self-supervised video representation learning based on Masked Video Modeling
(MVM) has demonstrated promising results for action recognition. However, existing …

This study describes an AI model by leveraging advanced Convolutional Neural Networks
(CNNs) to recognize affective states in real-world sports settings, particularly tennis matches …

Fall detection is a vital task in health monitoring, as it allows the system to trigger an alert
and therefore enable faster interventions when a person experiences a fall. Although most …

Advances in mmWave-based sensing have enabled a privacy-friendly approach to pose
and gesture recognition. Yet, providing robustness with the sparsity of reflected signals has …

In this paper, we tackle the new task of video-based Activated Muscle Group Estimation
(AMGE) aiming at identifying active muscle regions during physical activity. To this intent, we …

Considering the close connection between action recognition and human pose estimation,
we design a Collaboratively Self-supervised Video Representation (CSVR) learning …

Synthetic data generation is a proven method for augmenting training sets without the need
for extensive setups, yet its application in human activity recognition is underexplored. This …

Meta learning aims to endow models with the ability to quickly learn new tasks based on
existing knowledge. However, recent works have relied on complex structures and prior …