Jonas Wulff

Hi! I'm a Research Scientist at Xyla, where I'm working on Natural Language Processing.

From 2018-2021 I was a Postdoctoral Researcher with Antonio Torralba at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. My work concentrated on learning, understanding, and modifying the representations present inside of deep neural networks, with the goal of better applying them to hard tasks like video generation and understanding.

Prior to MIT, I did my PhD with Michael Black at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where I worked on optical flow and scene structure estimation.

Email: j o n a s @ x y l a . c o m | Google Scholar | Github


News

  • 10/2022
    I'm honored to receive the Koenderink Prize at this year's ECCV for our work on transforming the Sintel Open Movie into a benchmark and dataset for Optical Flow (and more!), together with Daniel Butler, Garrett Stanley, and Michael Black. For some background, Michael wrote an excellent blog post, revisiting Sintel after 10 years.
  • 09/2022
    Our paper on learning visual representations from procedural shaders got accepted to NeurIPS 2022.
  • 03/2022
    I'm co-organizing two workshops at ECCV 2022. The Robust Vision Challenge evaluates low- and mid-level vision algorithms across a spectrum of different datasets to test robustness and real-life usability. The workshop What is Motion for? will serve as a venue to discuss downstream uses and usefulness, representations, and challenges in motion estimation.
  • 09/2021
    I started a new position as a Research Scientist at Xyla, where I will be working on Natural Language Processing.
  • 09/2021
    Our paper on learning representations from noise got accepted to NeurIPS 2021.
  • 01/2021
    Our paper on compositionality in GANs got accepted to ICLR 2021.
  • 08/2020
    To compare cross-dataset performance across various vision tasks, we organized the second Workshop for Robust Vision in conjunction with ECCV 2020.
  • 07/2020
    The benchmark for single-image depth prediction for Sintel is now online.
    Please note that the benchmark is currently in beta stage and subject to change.

Publications

Procedural Image Programs for Representation Learning
Manel Baradad, Chun-Fu (Richard) Chen, Jonas Wulff, Tongzhou Wang, Rogerio Feris, Antonio Torralba, Phillip Isola
NeurIPS 2022 (to appear)
Paper (coming soon) | Website


Learning to See by Looking at Noise
Manel Baradad*, Jonas Wulff*, Tongzhou Wang, Phillip Isola, Antonio Torralba
NeurIPS 2021 (Spotlight)
Paper | Website | Code


Using Latent Space Regression to Analyze and Leverage Compositionality in GANs
Lucy Chai, Jonas Wulff, Phillip Isola
ICLR 2021
Paper | Website | Code


Improving Inversion and Generation Diversity in StyleGAN using a Gaussianized Latent Space
Jonas Wulff and Antonio Torralba
arXiv Preprint
Paper


Seeing what a GAN cannot create
David Bau, Jun-Yan Zhu, Jonas Wulff, William Peebles, Hendrik Strobelt, Bolei Zhou, Antonio Torralba
International Conference on Computer Vision (ICCV) 2019
Paper | Website | Code


Semantic photo manipulation with a generative image prior
David Bau, Hendrik Strobelt, William Peebles, Jonas Wulff, Jun-Yan Zhu, Antonio Torralba
SIGGRAPH 2019
Paper | Website


Competitive Collaboration: Joint unsupervised learning of depth, camera motion, optical flow, and motion segmentation
Anurag Ranjan, Varun Jampani, Lukas Balles, Kiwan Kim, Deqing Sun, Jonas Wulff, Michael J. Black
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019
Paper | Code


Inverting layers of a large generator
David Bau, Jun-Yan Zhu, Jonas Wulff, William Peebles, Hendrik Strobelt, Bolei Zhou, Antonio Torralba
ICLR Workshop on Debugging Machine Learning Models 2019
Paper


Temporal interpolation as an unsupervised pretraining task for optical flow estimation
Jonas Wulff and Michael J. Black
German Conference for Pattern Recognition (GCPR) 2018
Paper


"What is Optical Flow for?": Workshop Results and Summary
Fatma Güney, Laura Sevilla-Lara, Deqing Sun, Jonas Wulff
ECCV 2018 Workshop: What is Optical Flow for?
Paper


Model-Based Optical Flow: Layers, Learning, and Geometry
Jonas Wulff
PhD Thesis, University of Tuebingen
Online version


Optical flow in mostly rigid scenes
Jonas Wulff, Laura Sevilla-Lara, Michael J. Black
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017
Paper | Supplemental Material | Website | Code


Slow flow: Exploiting high-speed cameras for accurate and diverse optical flow reference data
Joel Janai, Fatma Güney, Jonas Wulff, Michael J. Black, Andreas Geiger
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017
Paper | Supplemental Material | Website | Code


Smooth loops from unconstrained video
Laura Sevilla-Lara, Jonas Wulff, Kailan Sunkavalli, Eli Shechtman
Eurographics Symposium on Rendering 2015
Paper | Website


Efficient sparse-to-dense optical flow estimation using a learned basis and layers
Jonas Wulff, Michael J. Black
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2015.
Paper | Code


Modeling blurred video with layers
Jonas Wulff and Michael J. Black
European Conference on Computer Vision (ECCV) 2014
Paper | Supplemental Material | Website


A fully-connected layered model of foreground and background flow
Deqing Sun, Jonas Wulff, Erik Sudderth, Hans-Peter Pfister, Michael J. Black
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2013
Paper | Supplemental Material


A naturalistic open source movie for optical flow evaluation
Daniel J. Butler, Jonas Wulff, Gerit B. Stanley, Michael J. Black
European Conference on Computer Vision (ECCV) 2012
Paper | Supplemental Material | Benchmark Website


Lessons and Insights from creating a synthetic optical flow benchmark
Jonas Wulff, Daniel J. Butler, Gerit B. Stanley, Michael J. Black
ECCV Workshop on Unsolved Problems in Optical Flow and Stereo Estimation
Paper


Publications prior to 2012

Correspondence estimation from non-rigid motion information
Jonas Wulff, Thomas Lotz, Thomas Stehle, Til Aach, and Geoffrey Chase
SPIE Medical Imaging 2011
Paper


Modellbasierte Echtzeit-Bewegungsschätzung in der Fluoreszenzendoskpie
Thomas Stehle, Jonas Wulff, Alexander Behrens, Sebasitan Gross, Til Aach
Bildverarbeitung für die Medizin 2010
Paper


Polyp segmentation in NBI colonoscopy
Sebastian Gross, Manuel Kennel, Thomas Stehle, Jonas Wulff, Jens Tischendorf, Christian Trautwein, Til Aach
Bildverarbeitung für die Medizing 2009
Publisher link


Denoising fluorescence endoscopy - A motion compensated temporal recursive video filter with an optimal minimum mean square error parameterization
Thomas Stehle, Jonas Wulff, Alexander Behrens, Sebastian Gross, Til Aach
ISBI 2009
Paper


Dynamic distortion correction for endoscopy systems with exchangeable optics
Thomas Stehle, Michael Hennes, Sebastian Gross, Alexander Behrens, Jonas Wulff, Til Aach
Bildverarbeitung für die Medizin 2009
Publisher link


Classification of colon polyps in NBI endoscopy using vascularization features
Thomas Stehle, Roland Auer, Sebastian Gross, Alexander Behrens, Jonas Wulff, Til Aach, Ron Winograd, Christian Trautwein, Jens Tischendorf, SPIE Medical Imaging 2009.
Publisher link


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