Efficient Video Action Recognition: How well does TriDet perform and generalize in a limited compute power and data setting?

In temporal action localization, given an input video, the goal is to predict the action that is present in the video, along with its temporal boundaries. Several powerful models have been proposed throughout the years, with transformer-based models achieving state-of-the-art performance in the recent months. Although novel models are becoming...

TemporalMaxer Performance in the Face of Constraint: A Study in Temporal Action Localization: A Comprehensive Analysis on the Adaptability of TemporalMaxer in Resource-Scarce Environments

This paper presents an analysis of the data and compute efficiency of the TemporalMaxer deep learning model in the context of temporal action localization (TAL), which involves accurately detecting the start and end times of specific video actions. The study explores the performance and scalability of the TemporalMaxer model under limited...

Assessing post-driving discomfort and its influence on gait patterns

Professional drivers need constant attention during long driving periods and sometimes perform tasks outside the truck. Driving discomfort may justify inattention, but it does not explain post-driving accidents outside the vehicle. This study aims to study the discomfort developed during driving by analysing modified preferred postures,...