Vision-based human action and activity recognition has an increasing importance among
the computer vision community with applications to visual surveillance, video retrieval and …

Multiple instance learning (MIL) is a form of weakly supervised learning where training
instances are arranged in sets, called bags, and a label is provided for the entire bag. This …

Ad-hoc video search (AVS) is an important yet challenging problem in multimedia retrieval.
Different from previous concept-based methods, we propose a fully deep learning method …

Multimedia event detection has been one of the major endeavors in video event analysis. A
variety of approaches have been proposed recently to tackle this problem. Among others …

Research on event-based processing and analysis of media is receiving an increasing
attention from the scientific community due to its relevance for an abundance of applications …

With the massive growth of social events in Internet, it has become more and more difficult to
exactly find and organize the interesting events from massive social media data, which is …

Crowd understanding has drawn increasing attention from the computer vision community,
and its progress is driven by the availability of public crowd datasets. In this paper, we …

Most of the research on human activity recognition has focused on learning a static model,
considering that all the training instances are labeled and present in advance, while in …

We focus on detecting complex events in unconstrained Internet videos. While most existing
works rely on the abundance of labeled training data, we consider a more difficult zero-shot …

This paper proposes a new video representation for few-example event recognition and
translation. Different from existing representations, which rely on either low-level features, or …