Philip Haeusser
Title
Cited by
Cited by
Year
Flownet: Learning optical flow with convolutional networks
A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ...
Proceedings of the IEEE international conference on computer vision, 2758-2766, 2015
2522*2015
A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
N Mayer, E Ilg, P Hausser, P Fischer, D Cremers, A Dosovitskiy, T Brox
Proceedings of the IEEE conference on computer vision and pattern …, 2016
12522016
Associative Domain Adaptation
P Haeusser, T Frerix, A Mordvintsev, D Cremers
In IEEE International Conference on Computer Vision (ICCV), 2017
1692017
Purcell-enhanced single-photon emission from nitrogen-vacancy centers coupled to a tunable microcavity
H Kaupp, T Hümmer, M Mader, B Schlederer, J Benedikter, P Haeusser, ...
Physical Review Applied 6 (5), 054010, 2016
123*2016
Learning by Association - A versatile semi-supervised training method for neural networks
P Häusser, A Mordvintsev, D Cremers
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
832017
Associative Deep Clustering: Training a Classification Network with no Labels
P Haeusser, J Plapp, V Golkov, E Aljalbout, D Cremers
Proc. of the German Conference on Pattern Recognition (GCPR), 2018
672018
vd Smagt P, Cremers D, Brox T (2015) Flownet: Learning optical flow with convolutional networks
A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazirbas, V Golkov
Proc. of the IEEE International Conf. on Computer Vision (ICCV), 0
13
Better text understanding through image-to-text transfer
K Kurach, S Gelly, M Jastrzebski, P Haeusser, O Teytaud, D Vincent, ...
arXiv preprint arXiv:1705.08386, 2017
62017
Golkov,“
A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazirbas
FlowNet: Learning Optical Flow with Convolutional Networks,” in ICCV 2, 2015
22015
Systems, Devices, Components and Methods for Detecting the Locations of Sources of Cardiac Rhythm Disorders in a Patient's Heart
P Haeusser, P Ruppersberg
US Patent App. 16/931,844, 2020
12020
Semi-supervised training of neural networks
P Haeusser, A Mordvintsev
US Patent App. 16/461,287, 2020
12020
Learning by Association
P Häusser
Technische Universität München, 2018
12018
Methods, Systems, Devices, and Components for Visualizing Electrographic Flow (EGF)
DE Luksic, P Haeusser, P Ruppersberg
US Patent App. 16/918,588, 2021
2021
Systems, Devices, Components and Methods for Detecting the Locations of Sources of Cardiac Rhythm Disorders in a Patient's Heart
P Haeusser, P Ruppersberg
US Patent App. 16/724,254, 2020
2020
Associative Deep Clustering: Training a Classification Network with No Labels
D Cremers
Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany …, 2019
2019
Herstellung und Charakterisierung von silberbeschichteten faserbasierten Fabry-Pérot Mikroresonatoren/Production and Characterization of Silver-Coated Fiber-Based Fabry Pérot …
P Häusser
Ludwig Maximilian Universität München, 2013
2013
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Articles 1–16