Log In Sign Up

Learning Crisp Boundaries Using Deep Refinement Network and Adaptive Weighting Loss

by   Yi-Jun Cao, et al.

Significant progress has been made in boundary detection with the help of convolutional neural networks. Recent boundary detection models not only focus on real object boundary detection but also "crisp" boundaries (precisely localized along the object's contour). There are two methods to evaluate crisp boundary performance. One uses more strict tolerance to measure the distance between the ground truth and the detected contour. The other focuses on evaluating the contour map without any postprocessing. In this study, we analyze both methods and conclude that both methods are two aspects of crisp contour evaluation. Accordingly, we propose a novel network named deep refinement network (DRNet) that stacks multiple refinement modules to achieve richer feature representation and a novel loss function, which combines cross-entropy and dice loss through effective adaptive fusion. Experimental results demonstrated that we achieve state-of-the-art performance for several available datasets.


page 7

page 9


Contour Dice loss for structures with Fuzzy and Complex Boundaries in Fetal MRI

Volumetric measurements of fetal structures in MRI are time consuming an...

Photo-Sketching: Inferring Contour Drawings from Images

Edges, boundaries and contours are important subjects of study in both c...

Contour Loss: Boundary-Aware Learning for Salient Object Segmentation

We present a learning model that makes full use of boundary information ...

SharpContour: A Contour-based Boundary Refinement Approach for Efficient and Accurate Instance Segmentation

Excellent performance has been achieved on instance segmentation but the...

Contour location via entropy reduction leveraging multiple information sources

We introduce an algorithm to locate contours of functions that are expen...

Distance Map Loss Penalty Term for Semantic Segmentation

Convolutional neural networks for semantic segmentation suffer from low ...

Coronary Wall Segmentation in CCTA Scans via a Hybrid Net with Contours Regularization

Providing closed and well-connected boundaries of coronary artery is ess...