Abstract Recently, deep Convolutional Neural Networks (CNNs) can achieve human-level
performance in edge detection with the rich and abstract edge representation capacities …

Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

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 …

Exploiting multi-scale representations is critical to improve edge detection for objects at
different scales. To extract edges at dramatically different scales, we propose a Bi …

In this paper, we propose an accurate edge detector using richer convolutional features
(RCF). Since objects in natural images possess various scales and aspect ratios, learning …

Object detection is a basic issue of very high-resolution remote sensing images (RSIs) for
automatically labeling objects. At present, deep learning has gradually gained the …

Edge detection is a critical component of many vision systems, including object detectors
and image segmentation algorithms. Patches of edges exhibit well-known forms of local …

Contour detection serves as the basis of a variety of computer vision tasks such as image
segmentation and object recognition. The mainstream works to address this problem focus …

Glimpse is a continuous, real-time object recognition system for camera-equipped mobile
devices. Glimpse captures full-motion video, locates objects of interest, recognizes and …

We review the work on data-driven grasp synthesis and the methodologies for sampling and
ranking candidate grasps. We divide the approaches into three groups based on whether …