Recognizing the actions, plans, and goals of a person in an unconstrained environment is a
key feature that future robotic systems will need in order to achieve a natural human …

Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …

The growing number of action classes has posed a new challenge for video understanding,
making Zero-Shot Action Recognition (ZSAR) a thriving direction. The ZSAR task aims to …

Abstract Human Action Recognition (HAR) has achieved a remarkable milestone in the field
of computer vision. Apart from its varied applications in human–computer interactions …

We present a cross-modal Transformer-based framework, which jointly encodes video data
and text labels for zero-shot action recognition (ZSAR). Our model employs a conceptually …

Although video summarization has achieved tremendous success benefiting from Recurrent
Neural Networks (RNN), RNN-based methods neglect the global dependencies and multi …

The Activity Recognition Chain generally precludes the challenging scenario of recognizing
new activities that were unseen during training, despite this scenario being a practical and …

The goal of zero-shot action recognition (ZSAR) is to classify action classes which were not
previously seen during training. Traditionally, this is achieved by training a network to map …

Abstract Video-language models (VLMs), large models pre-trained on numerous but noisy
video-text pairs from the internet, have revolutionized activity recognition through their …

In vision-based action recognition, spatio-temporal features from different modalities are
used for recognizing activities. Temporal modeling is a long challenge of action recognition …