Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …

Video description is the automatic generation of natural language sentences that describe
the contents of a given video. It has applications in human-robot interaction, hel** the …

This paper studies the BERT pretraining of video transformers. It is a straightforward but
worth-studying extension given the recent success from BERT pretraining of image …

In recent years, the abuse of a face swap technique called deepfake has raised enormous
public concerns. So far, a large number of deepfake videos (known as" deepfakes") have …

Benefiting from masked visual modeling, self-supervised video representation learning has
achieved remarkable progress. However, existing methods focus on learning …

In this paper, we introduce a novel visual representation learning which relies on a handful
of adaptively learned tokens, and which is applicable to both image and video …

Despite the steady progress in video analysis led by the adoption of convolutional neural
networks (CNNs), the relative improvement has been less drastic as that in 2D static image …

The state of the art in video understanding suffers from two problems:(1) The major part of
reasoning is performed locally in the video, thus missing important relationships within …

With the rapid development of Deepfake synthesis technology, our information security and
personal privacy have been severely threatened in recent years. To achieve a robust …

Many recent advancements in Computer Vision are attributed to large datasets. Open-
source software packages for Machine Learning and inexpensive commodity hardware …