Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

The age of big data is now coming. But the traditional data analytics may not be able to
handle such large quantities of data. The question that arises now is, how to develop a high …

With the increasing interest in pedestrian detection, pedestrian datasets have also been the
subject of research in the past decades. However, most existing datasets focus on a color …

Generalizing deep neural networks to new target domains is critical to their real-world utility.
In practice, it may be feasible to get some target data labeled, but to be cost-effective it is …

Computer vision applications have come to rely increasingly on superpixels in recent years,
but it is not always clear what constitutes a good superpixel algorithm. In an effort to …

VLFeat is an open and portable library of computer vision algorithms. It aims at facilitating
fast prototy** and reproducible research for computer vision scientists and students. It …

Word embeddings are numeric representations of meaning derived from word co-
occurrence statistics in corpora of human-produced texts. The statistical regularities in …

Decision forests (also known as random forests) are an indispensable tool for automatic
image analysis. This practical and easy-to-follow text explores the theoretical underpinnings …

We present two modifications to the popular k-means clustering algorithm to address the
extreme requirements for latency, scalability, and sparsity encountered in user-facing web …

Superpixels are becoming increasingly popular for use in computer vision applications.
However, there are few algorithms that output a desired number of regular, compact …