activity
20162021
most citedREFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

858 citations · 914 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20213 cited

Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization

Haoyu Ma, Xiangru Lin, Zifeng Wu +1

Unsupervised domain adaptation (UDA) in semantic segmentation is a fundamental yet promising task relieving the need for laborious annotation works. However, the domain shifts/disc…

cs.CV2019858 cited

REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

José Ignacio Orlando, Huazhu Fu, João Barbossa Breda +28

Glaucoma is one of the leading causes of irreversible but preventable blindness in working age populations. Color fundus photography (CFP) is the most cost-effective imaging modali…

cs.CV201753 cited

Real-time Semantic Image Segmentation via Spatial Sparsity

Zifeng Wu, Chunhua Shen, Anton van den Hengel

We propose an approach to semantic (image) segmentation that reduces the computational costs by a factor of 25 with limited impact on the quality of results. Semantic segmentation…

cs.CV2016

Bridging Category-level and Instance-level Semantic Image Segmentation

Zifeng Wu, Chunhua Shen, Anton van den Hengel

We propose an approach to instance-level image segmentation that is built on top of category-level segmentation. Specifically, for each pixel in a semantic category mask, its corre…

cs.CV2016

High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks

Zifeng Wu, Chunhua Shen, Anton van den Hengel

We propose a method for high-performance semantic image segmentation (or semantic pixel labelling) based on very deep residual networks, which achieves the state-of-the-art perform…