The world we see is ever-changing and it always changes with people, things, and the
environment. Domain is referred to as the state of the world at a certain moment. A research …

Cross-domain learning methods have shown promising results by leveraging labeled
patterns from the auxiliary domain to learn a robust classifier for the target domain which has …

Sparse coding which encodes the original signal in a sparse signal space, has shown its
state-of-the-art performance in the visual codebook generation and feature quantization …

We propose a visual event recognition framework for consumer videos by leveraging a large
amount of loosely labeled web videos (eg, from YouTube). Observing that consumer videos …

In this paper, we present an image parsing to text description (I2T) framework that generates
text descriptions of image and video content based on image understanding. The proposed …

Cross-domain learning methods have shown promising results by leveraging labeled
patterns from auxiliary domains to learn a robust classifier for target domain, which has a …

The Bag-of-visual Words (BoW) image representation has been applied for various
problems in the fields of multimedia and computer vision. The basic idea is to represent …

The goal of high-level event recognition is to automatically detect complex high-level events
in a given video sequence. This is a difficult task especially when videos are captured under …

We address the problem of visual knowledge adaptation by leveraging labeled patterns from
source domain and a very limited number of labeled instances in target domain to learn a …

Visual data such as images and videos are easily accessible nowadays, and they play
critical roles in many real-world applications like surveillance. This raises a series of …