Philip Häusser

According to our database, Philip Häusser authored at least 8 papers between 2015 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Spatio-Temporal Activation Wavefront Reconstruction From Sparsely Sampled Electrograms.

Kostiantyn Ahapov, Peter Ruppersberg, Philip Häusser, Melissa H. Kong, Michael Möller

IEEE Trans. Biomed. Eng., September, 2025

2018

Learning by Association: Strategies for solving computer vision tasks with less labeled data.

Philip Häusser

PhD thesis, 2018

Associative Deep Clustering: Training a Classification Network with No Labels.

Philip Häusser, Johannes Plapp, Vladimir Golkov, Elie Aljalbout, Daniel Cremers

Proceedings of the Pattern Recognition - 40th German Conference, 2018

2017

Better Text Understanding Through Image-To-Text Transfer.

Karol Kurach, Sylvain Gelly, Michal Jastrzebski, Philip Häusser, Olivier Teytaud, Damien Vincent, Olivier Bousquet

CoRR, 2017

Associative Domain Adaptation.

Philip Häusser, Thomas Frerix, Alexander Mordvintsev, Daniel Cremers

Proceedings of the IEEE International Conference on Computer Vision, 2017

Learning by Association - A Versatile Semi-Supervised Training Method for Neural Networks.

Philip Häusser, Alexander Mordvintsev, Daniel Cremers

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation.

Nikolaus Mayer, Eddy Ilg, Philip Häusser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

FlowNet: Learning Optical Flow with Convolutional Networks.

Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015