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Hypothesis: Nowadays, the number of people suffering from shoulder osteoarthritis increases as the population is ageing. An end-stage treatment is the total shoulder arthroplasty (TSA), but it still suffers from a high failure rate in comparison to other j ...
Semantic segmentation algorithms that can robustly segment objects across multiple camera viewpoints are crucial for assuring navigation and safety in emerging applications such as autonomous driving. Existing algorithms treat each image in isolation, but ...
A large part of computer vision research is devoted to building models
and algorithms aimed at understanding human appearance and behaviour
from images and videos. Ultimately, we want to build automated systems
that are at least as capable as people when i ...
Keyword-based image color re-rendering is a convenient way to enhance the color of images. Most methods only focus on the color characteristics of the image while ignoring the semantic meaning of different regions. We propose to incorporate semantic inform ...
Apartment searching has been a hot demand all over the world. Understanding the apartment structure will significantly contribute to simplifying the searching process. In this project, the fully convolutional networks are applied to generate semantic segme ...
Keyphrase extraction is the task of automatically selecting a small set of phrases that best describe a given free text document. Keyphrases can be used for indexing, searching, aggregating and summarizing text documents, serving many automatic as well as ...
Human ability to foresee the near future plays a key role in everyone's life to prevent potentially dangerous situations. To be able to make predictions is crucial when people have to interact with the surrounding environment. Modeling such capability can ...
This study deals with semantic segmentation of high-resolution (aerial) images where a semantic class label is assigned to each pixel via supervised classification as a basis for automatic map generation. Recently, deep convolutional neural networks (CNNs) ...
Institute of Electrical and Electronics Engineers2017
Semantically describing the contents of images is one of the classical problems of computer vision. With huge numbers of images being made available daily, there is increasing interest in methods for semantic pixel labelling that exploit large image sets. ...
We propose a head pose invariant gaze estimation model for distant RGB-D cameras. It relies on a geometric understanding of the 3D gaze action and generation of eye images. By introducing a semantic segmentation of the eye region within a generative proces ...