Search Results for author: Özgün Çiçek

Found 6 papers, 5 papers with code

Parting with Illusions about Deep Active Learning

no code implementations11 Dec 2019 Sudhanshu Mittal, Maxim Tatarchenko, Özgün Çiçek, Thomas Brox

Active learning aims to reduce the high labeling cost involved in training machine learning models on large datasets by efficiently labeling only the most informative samples.

Active Learning Data Augmentation +2

Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow

1 code implementation ECCV 2018 Eddy Ilg, Özgün Çiçek, Silvio Galesso, Aaron Klein, Osama Makansi, Frank Hutter, Thomas Brox

Optical flow estimation can be formulated as an end-to-end supervised learning problem, which yields estimates with a superior accuracy-runtime tradeoff compared to alternative methodology.

Optical Flow Estimation

3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

16 code implementations21 Jun 2016 Özgün Çiçek, Ahmed Abdulkadir, Soeren S. Lienkamp, Thomas Brox, Olaf Ronneberger

This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images.

Ranked #12 on 3D Instance Segmentation on ScanNet(v2) (Mean AP @ 0.5 metric)

3D Instance Segmentation Data Augmentation

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