| A naturalistic open source movie for optical flow evaluation DJ Butler, J Wulff, GB Stanley, MJ Black European conference on computer vision, 611-625, 2012 | 2705 | 2012 |
| 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 | 774 | 2019 |
| 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 | 493 | 2019 |
| 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 | 429 | 2020 |
| 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 | 236 | 2015 |
| Do we still need clinical language models? E Lehman, E Hernandez, D Mahajan, J Wulff, MJ Smith, Z Ziegler, ... Conference on health, inference, and learning, 578-597, 2023 | 188 | 2023 |
| Optical flow in mostly rigid scenes J Wulff, L Sevilla-Lara, MJ Black Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 152 | 2017 |
| 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 | 145 | 2021 |
| 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 | 125 | 2013 |
| Modeling blurred video with layers J Wulff, MJ Black European conference on computer vision, 236-252, 2014 | 112 | 2014 |
| Lessons and insights from creating a synthetic optical flow benchmark J Wulff, DJ Butler, GB Stanley, MJ Black European conference on computer vision, 168-177, 2012 | 108 | 2012 |
| 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 | 104 | 2017 |
| Using latent space regression to analyze and leverage compositionality in gans L Chai, J Wulff, P Isola arXiv preprint arXiv:2103.10426, 2021 | 95 | 2021 |
| 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 | 87 | 2009 |
| 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 | 67 | 2009 |
| 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 | 61 | 2019 |
| Improving inversion and generation diversity in stylegan using a gaussianized latent space J Wulff, A Torralba arXiv preprint arXiv:2009.06529, 2020 | 51 | 2020 |
| Procedural image programs for representation learning M Baradad, R Chen, J Wulff, T Wang, R Feris, A Torralba, P Isola Advances in Neural Information Processing Systems 35, 6450-6462, 2022 | 42 | 2022 |
| 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 | 42 | 2018 |
| 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 | 25 | 2012 |
Michael J. BlackMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
