Benchmarking Data and Computational Efficiency of ActionFormer on Temporal Action Localization Tasks: Analysing the Performance and Generalizability of ActionFormer in Resource-constrained Environments

In temporal action localization, given an input video, the goal is to predict which actions it contains, where they begin and where they end. Training and testing current state-of-the-art, deep learning models is done assuming access to large amounts of data and computational power. Gathering such data is however a challenging task and access to...