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Jonas Wulff
Jonas Wulff
Postdoctoral Researcher, MIT CSAIL
Verified email at csail.mit.edu
Title
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Cited by
Year
A naturalistic open source movie for optical flow evaluation
DJ Butler, J Wulff, GB Stanley, MJ Black
Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012
21532012
Competitive collaboration: Joint unsupervised learning of depth, camera motion, optical flow and motion segmentation
A Ranjan, V Jampani, L Balles, K Kim, D Sun, J Wulff, MJ Black
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
6212019
Semantic photo manipulation with a generative image prior
D Bau, H Strobelt, W Peebles, J Wulff, B Zhou, JY Zhu, A Torralba
arXiv preprint arXiv:2005.07727, 2020
3382020
Seeing what a gan cannot generate
D Bau, JY Zhu, J Wulff, W Peebles, H Strobelt, B Zhou, A Torralba
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
3172019
Efficient sparse-to-dense optical flow estimation using a learned basis and layers
J Wulff, MJ Black
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
2012015
Optical flow in mostly rigid scenes
J Wulff, L Sevilla-Lara, MJ Black
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
1322017
A fully-connected layered model of foreground and background flow
D Sun, J Wulff, EB Sudderth, H Pfister, MJ Black
Proceedings of the IEEE conference on computer vision and pattern …, 2013
1162013
Modeling blurred video with layers
J Wulff, MJ Black
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
1002014
Slow flow: Exploiting high-speed cameras for accurate and diverse optical flow reference data
J Janai, F Guney, J Wulff, MJ Black, A Geiger
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
882017
Lessons and insights from creating a synthetic optical flow benchmark
J Wulff, DJ Butler, GB Stanley, MJ Black
Computer Vision–ECCV 2012. Workshops and Demonstrations: Florence, Italy …, 2012
882012
Classification of colon polyps in NBI endoscopy using vascularization features
T Stehle, R Auer, S Gross, A Behrens, J Wulff, T Aach, R Winograd, ...
Medical Imaging 2009: Computer-Aided Diagnosis 7260, 774-785, 2009
812009
Learning to see by looking at noise
M Baradad Jurjo, J Wulff, T Wang, P Isola, A Torralba
Advances in Neural Information Processing Systems 34, 2556-2569, 2021
742021
Using latent space regression to analyze and leverage compositionality in gans
L Chai, J Wulff, P Isola
arXiv preprint arXiv:2103.10426, 2021
642021
Do we still need clinical language models?
E Hernandez, D Mahajan, J Wulff, MJ Smith, Z Ziegler, D Nadler, ...
Conference on Health, Inference, and Learning, 578-597, 2023
562023
Polyp segmentation in NBI colonoscopy
S Gross, M Kennel, T Stehle, J Wulff, J Tischendorf, C Trautwein, T Aach
Bildverarbeitung für die Medizin 2009: Algorithmen—Systeme—Anwendungen …, 2009
502009
Inverting layers of a large generator
D Bau, JY Zhu, J Wulff, W Peebles, H Strobelt, B Zhou, A Torralba
ICLR workshop 2 (3), 4, 2019
452019
Adversarial collaboration: Joint unsupervised learning of depth, camera motion, optical flow and motion segmentation
A Ranjan, V Jampani, K Kim, D Sun, J Wulff, MJ Black
arXiv preprint arXiv:1805.09806 2 (6), 2018
392018
Improving inversion and generation diversity in stylegan using a gaussianized latent space
J Wulff, A Torralba
arXiv preprint arXiv:2009.06529, 2020
362020
Semantic photo manipulation with a generative image prior
D Bau, H Strobelt, W Peebles, J Wulff, B Zhou, JY Zhu, A Torralba
21
MPI-Sintel optical flow benchmark: Supplemental material
D Butler, J Wulff, G Stanley, M Black
MPI-IS-TR-006, MPI for Intelligent Systems (2012, 2012
182012
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