Object detection and tracking is one of the most important and challenging branches in
computer vision, and have been widely applied in various fields, such as health-care …

Due to object detection's close relationship with video analysis and image understanding, it
has attracted much research attention in recent years. Traditional object detection methods …

Optical remote sensing images (RSIs) have been widely used in many applications, and one
of the interesting issues about optical RSIs is the salient object detection (SOD). However …

Object detection, including objectness detection (OD), salient object detection (SOD), and
category-specific object detection (COD), is one of the most fundamental yet challenging …

How to incorporate cross-modal complementarity sufficiently is the cornerstone question for
RGB-D salient object detection. Previous works mainly address this issue by simply …

Low-level saliency cues or priors do not produce good enough saliency detection results
especially when the salient object presents in a low-contrast background with confusing …

Most existing bottom-up methods measure the foreground saliency of a pixel or region
based on its contrast within a local context or the entire image, whereas a few methods focus …

In this paper, we introduce Cellular Automata--a dynamic evolution model to intuitively
detect the salient object. First, we construct a background-based map using color and space …

Salient object detection has been attracting a lot of interest, and recently various heuristic
computational models have been designed. In this paper, we regard saliency map …

A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse
coding is presented. In addition to using class labels of training data, we also associate label …