Skip to search formSkip to main contentSkip to account menu
Region filling and object removal by exemplar-based image inpainting
TLDR
The simultaneous propagation of texture and structure information is achieved by a single, efficient algorithm that combines the advantages of two approaches: exemplar-based texture synthesis and block-based sampling process.
View on IEEE
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
TLDR
The set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences are reported, finding that different algorithms worked best for different sub-regions, but that no single algorithm ranked in the top for all sub-Regions simultaneously.
View on IEEE
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
TLDR
A new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently, is proposed, which is used for automatic visual recognition and semantic segmentation of photographs.
View via Publisher
TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context
TLDR
A new approach for learning a discriminative model of object classes, incorporating texture, layout, and context information efficiently, which gives competitive and visually pleasing results for objects that are highly textured, highly structured, and even articulated.
View on Springer
Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images
We address the problem of inferring the pose of an RGB-D camera relative to a known 3D scene, given only a single acquired image. Our approach employs a regression forest that is capable of inferring…
View on IEEE
Object categorization by learned universal visual dictionary
TLDR
An optimally compact visual dictionary is learned by pair-wise merging of visual words from an initially large dictionary, and a novel statistical measure of discrimination is proposed which is optimized by each merge operation.
View on IEEE
Object removal by exemplar-based inpainting
TLDR
A best-first algorithm in which the confidence in the synthesized pixel values is propagated in a manner similar to the propagation of information in inpainting, which demonstrates the effectiveness of the algorithm in removing large occluding objects as well as thin scratches.
View on IEEE
Geodesic star convexity for interactive image segmentation
TLDR
A new shape constraint for interactive image segmentation is introduced, an extension of Veksler's star-convexity prior, in two ways: from a single star to multiple stars and from Euclidean rays to Geodesic paths.
View on IEEE
Deep Neural Decision Forests
TLDR
A novel approach that unifies classification trees with the representation learning functionality known from deep convolutional networks, by training them in an end-to-end manner by introducing a stochastic and differentiable decision tree model.
View on IEEE
Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning
TLDR
A unified, efficient model of random decision forests which can be applied to a number of machine learning, computer vision, and medical image analysis tasks is presented and relative advantages and disadvantages discussed.
View via Publisher
...
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License