Vision-based human action and activity recognition has an increasing importance among
the computer vision community with applications to visual surveillance, video retrieval and …

Human activity recognition is an important area of computer vision research. Its applications
include surveillance systems, patient monitoring systems, and a variety of systems that …

Background Active PTZ cameras serve as a practical alternative to high-resolution
omnidirectional cameras in wide-area surveillance systems. On the one hand, flexible pan …

Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …

In recent years, considerable progress on the task of text-video retrieval has been achieved
by leveraging large-scale pretraining on visual and audio datasets to construct powerful …

Temporal action localization is an important yet challenging problem. Given a long,
untrimmed video consisting of multiple action instances and complex background contents …

Current state-of-the-art approaches for spatio-temporal action localization rely on detections
at the frame level that are then linked or tracked across time. In this paper, we leverage the …

Optical flow computation is a key component in many computer vision systems designed for
tasks such as action detection or activity recognition. However, despite several major …

We present a deep-learning framework for real-time multiple spatio-temporal (S/T) action
localisation and classification. Current state-of-the-art approaches work offline, and are too …

We consider the automated recognition of human actions in surveillance videos. Most
current methods build classifiers based on complex handcrafted features computed from the …