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Superpixel Algorithms Compared using NVD3.js - David Stutz
http://davidstutz.de/superpixel-algorithms-compared-using-nvd3-js
Superpixel Algorithms Compared using NVD3.js. The comparison of superpixel algorithms presented in my bachelor thesis “Superpixel Segmentation using Depth Information” as interactive plots using nvd3. After completing my bachelor thesis about superpixel segmentation at the Computer Vision Group at RWTH Aachen University, I thought about an interactive visualization of the results. Finally, I used nvd3. To create the visualizations presented below. The following superpixel algorithms are compared:. As sho...
Projects - David Stutz
http://davidstutz.de/projects
This page presents an extensive comparison of several state-of-the-art superpixel algorithms using an extended version of the Berkeley Segmentation Benchmark [2] as well as a new implementation of the superpixels algorithm called SEEDS [1]. Mdash; Extended Berkeley Segmentation Benchmark. Mdash; Superpixel Algorithms: Overview. Mdash; Berkeley Segmentation Dataset. Mdash; Nyu Depth V2 Dataset. Mdash; NYU Depth V2 Tools. Mdash; SEEDS Superpixels. Mdash; SLIC Superpixels. Mdash; DASP Superpixels. Kohana is...
Ming-Yu Liu
http://aliensunmin.github.io/project/accv16tutorial/index.html
Senior Research Scientist at Nvidia Research. Assistant Professor in Electrical Engineering. At National Tsing Hua University. Date: Nov. 24. Introduction to deep learning in computer vision. We will introduce the standard supervised deep learning model such as CNN and RNN. The introduction will include: a brief history of the development of both models, their model architectures and intuition, training methods and tips for learning a good model. Deep learning for vision and language. Ming-Yu Liu and Onc...
Superpixels/SEEDS - David Stutz
http://davidstutz.de/projects/superpixelsseeds
JavaScript / Twitter Bootstrap. Extended Berkeley Segmentation Benchmark. Nyu Depth V2 Dataset. NYU Depth V2 Tools. CIS and CS Superpixels. Comparison of State-Of-The-Art Superpixel Algorithms. The results have been published at the Young Researcher Forum of GCPR 2015! Paper (∼ 2.7MB). Poster (∼ 7.2MB). The final publication is available at link.springer.com. Details can be found below. LaTeX source of the bachelor thesis and the slides, as well as the code for evaluation is now available on GitHub.
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