Abstract Weakly-supervised Temporal Action Localization (WTAL) attempts to localize the
actions in untrimmed videos using only video-level supervision. Most recent works approach …

Visual private information leakage is an emerging key issue for the fast growing applications
of video understanding like activity recognition. Existing approaches for mitigating privacy …

Online action detection in surveillance scenarios presents considerable challenges,
particularly due to the dynamically changing environments and real-time processing …

Spatio-temporal action detection (STAD) aims to classify the actions present in a video and
localize them in space and time. It has become a particularly active area of research in …

Abstract Semi-Supervised Learning can be more beneficial for the video domain compared
to images because of its higher annotation cost and dimensionality. Besides, any video …

This paper explores the impact of occlusions in video action detection. We facilitatethis study
by introducing five new benchmark datasets namely O-UCF and O-JHMDB consisting of …

Deep learning has made significant strides in video understanding tasks, but the
computation required to classify lengthy and massive videos using clip-level video …

Drone-to-drone detection using visual feed has crucial applications, such as detecting drone
collisions, detecting drone attacks, or coordinating flight with other drones. However, existing …

Current methods for spatiotemporal action tube detection often extend a bounding box
proposal at a given key-frame into a 3D temporal cuboid and pool features from nearby …

Temporal video alignment aims to synchronize the key events like object interactions or
action phase transitions in two videos. Such methods could benefit various video editing …