output
20112026
most citedREFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

858 citations

Showing 2018Show all

18 papers · 1 filter

cs.CV2018

Scalable Deep -Subspace Clustering

Tong Zhang, Pan Ji, Mehrtash Harandi +2

Subspace clustering algorithms are notorious for their scalability issues because building and processing large affinity matrices are demanding. In this paper, we introduce a metho…

cs.CV2018★ 6 cited

Phase-only Image Based Kernel Estimation for Single-image Blind Deblurring

Liyuan Pan, Richard Hartley, Miaomiao Liu +1

The image blurring process is generally modelled as the convolution of a blur kernel with a latent image. Therefore, the estimation of the blur kernel is essentially important for…

cs.CV2018★ 44 cited

Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition

Hui Li, Peng Wang, Chunhua Shen +1

Recognizing irregular text in natural scene images is challenging due to the large variance in text appearance, such as curvature, orientation and distortion. Most existing approac…

cs.CV2018★ 1 cited

Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks

Zhibin Liao, Tom Drummond, Ian Reid +1

In this paper, we introduce a novel methodology for characterising the performance of deep learning networks (ResNets and DenseNet) with respect to training convergence and general…

math.OC2018

A Geometric Observer for Scene Reconstruction Using Plenoptic Cameras

Sean G. P. O'Brien, Jochen Trumpf, Viorela Ila +1

This paper proposes an observer for generating depth maps of a scene from a sequence of measurements acquired by a two-plane light-field (plenoptic) camera. The observer is based o…

cs.CV2018★ 1 cited

3D Geometry-Aware Semantic Labeling of Outdoor Street Scenes

Yiran Zhong, Yuchao Dai, Hongdong Li

This paper is concerned with the problem of how to better exploit 3D geometric information for dense semantic image labeling. Existing methods often treat the available 3D geometry…