Instance segmentation in 3D scenes is fundamental in many applications of scene
understanding. It is yet challenging due to the compound factors of data irregularity and …

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 …

Superpixels group perceptually similar pixels to create visually meaningful entities while
heavily reducing the number of primitives for subsequent processing steps. As of these …

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 …

We propose a unified approach for bottom-up hierarchical image segmentation and object
candidate generation for recognition, called Multiscale Combinatorial Grou** (MCG). For …

We propose a unified approach for bottom-up hierarchical image segmentation and object
proposal generation for recognition, called Multiscale Combinatorial Grou** (MCG). For …

We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented
contours and region hierarchies starting from generic image classification Convolutional …

We introduce a differentiable, end-to-end trainable framework for solving pixel-level
grou** problems such as instance segmentation consisting of two novel components …

Abstract We present Convolutional Oriented Boundaries (COB), which produces multiscale
oriented contours and region hierarchies starting from generic image classification …