Object class detection, also known as category-level object detection, has become one of
the most focused areas in computer vision in the new century. This article attempts to …

Recently, image representation built upon Convolutional Neural Network (CNN) has been
shown to provide effective descriptors for image search, outperforming pre-CNN features as …

In this paper, we address the task of object counting in images. We follow modern learning
approaches in which a density map is estimated directly from the input image. We employ …

We propose a new supervised learning framework for visual object counting tasks, such as
estimating the number of cells in a microscopic image or the number of humans in …

行人检测是计算机视觉中的研究热点和难点, 本文对2005-2011 这段时间内的行人检测技术中
最核心的两个问题—特征提取, 分类器与定位—的研究现状进行综述. 文章中首先将这些问题的 …

In recent years, many research works have been carried out to recognize human actions
from video clips. To learn an effective action classifier, most of the previous approaches rely …

Automatic inspection of X-ray scans at security checkpoints can improve the public security.
X-ray images are different from photographic images. They are transparent. They contain …

In this work, we address the problem of spatio-temporal action detection in temporally
untrimmed videos. It is an important and challenging task as finding accurate human actions …

The Fisher vector (FV) representation is a high-dimensional extension of the popular bag-of-
word representation. Transformation of the FV by power and L2 normalizations has shown to …

We propose a sequential optimization technique for segmenting a rectified image of a
facade into semantic categories. Our method retrieves a parsing which respects common …