Abstract Human Action Recognition from Unmanned Aerial Vehicles is a dynamic research
domain with significant benefits in scale, mobility, deployment, and covert observation. This …

We present a new learning approach, Soft Conditional Prompt Learning (SCP), which
leverages the strengths of prompt learning for aerial video action recognition. Our approach …

Dynamic contextual attribute information in the time dimension is the key to fine-grained
action recognition. Temporal contextual relationships cannot be captured by conventional …

We present a new general learning approach, Prompt Learning for Action Recognition
(PLAR), which leverages the strengths of prompt learning to guide the learning process. Our …

Unmanned Aerial Vehicles (UAV) have revolutionized human action recognition by offering
a bird's-eye perspective, thereby unlocking unprecedented potential for comprehensive …

We introduce SOAR, a novel Self-supervised pretraining algorithm for aerial footage
captured by Unmanned Aerial Vehicles (UAVs). We incorporate human object knowledge …

The Chinese stock market, marked by rapid growth and significant volatility, presents unique
challenges for investors and analysts. A-share stocks, traded on the Shanghai and …

Action recognition on unmanned aerial vehicles (UAVs) must cope with complex
backgrounds and focus on small targets. Existing methods usually use additional detectors …

Human Activity Recognition (HAR) systems aim to understand human behaviour and assign
a label to each action, attracting significant attention in computer vision due to their wide …

Frame sampling is a fundamental influence on the accuracy of video gesture recognition
due to the essential redundancy in time and limited computation resources. The existing …