1 code implementation • 19 Jan 2018 • Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox
The finding that very large networks can be trained efficiently and reliably has led to a paradigm shift in computer vision from engineered solutions to learning formulations.
3 code implementations • CVPR 2016 • Nikolaus Mayer, Eddy Ilg, Philip Häusser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox
By combining a flow and disparity estimation network and training it jointly, we demonstrate the first scene flow estimation with a convolutional network.
476 code implementations • 18 May 2015 • Olaf Ronneberger, Philipp Fischer, Thomas Brox
There is large consent that successful training of deep networks requires many thousand annotated training samples.
Ranked #1 on Semantic Segmentation on STARE
18 code implementations • ICCV 2015 • Philipp Fischer, Alexey Dosovitskiy, Eddy Ilg, Philip Häusser, Caner Hazırbaş, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox
Optical flow estimation has not been among the tasks where CNNs were successful.
1 code implementation • 26 Jun 2014 • Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, Martin Riedmiller, Thomas Brox
While such generic features cannot compete with class specific features from supervised training on a classification task, we show that they are advantageous on geometric matching problems, where they also outperform the SIFT descriptor.
no code implementations • 22 May 2014 • Philipp Fischer, Alexey Dosovitskiy, Thomas Brox
Surprisingly, convolutional neural networks clearly outperform SIFT on descriptor matching.