This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …

The booming Artificial Intelligence (AI) provides fertile ground for AI in education. So far, few
reviews have been deployed to explore how AI empowers English as Foreign Language …

Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

Abstract We present Ego-Exo4D a diverse large-scale multimodal multiview video dataset
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …

Contrastive learning-based video-language representation learning approaches, eg, CLIP,
have achieved outstanding performance, which pursue semantic interaction upon pre …

Procedural activity understanding requires perceiving human actions in terms of a broader
task, where multiple keysteps are performed in sequence across a long video to reach a …

There has been a recent explosion of large-scale image-text datasets, as images with alt-
text captions can be easily obtained online. Obtaining large-scale, high quality data for video …

Our goal in this paper is the adaptation of image-text models for long video retrieval. Recent
works have demonstrated state-of-the-art performance in video retrieval by adopting CLIP …

With the emergence of foundation models (FMs) that are trained on large amounts of data at
scale and adaptable to a wide range of downstream applications, AI is experiencing a …

Temporal action segmentation (TAS) in videos aims at densely identifying video frames in
minutes-long videos with multiple action classes. As a long-range video understanding task …