| Learning to adapt structured output space for semantic segmentation YH Tsai, WC Hung, S Schulter, K Sohn, MH Yang, M Chandraker Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 921 | 2018 |
| Fast and accurate image upscaling with super-resolution forests S Schulter, C Leistner, H Bischof Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 637 | 2015 |
| Domain adaptation for structured output via discriminative patch representations YH Tsai, K Sohn, S Schulter, M Chandraker Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 196 | 2019 |
| Deep network flow for multi-object tracking S Schulter, P Vernaza, W Choi, M Chandraker Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 178 | 2017 |
| You should use regression to detect cells P Kainz, M Urschler, S Schulter, P Wohlhart, V Lepetit International Conference on Medical Image Computing and Computer-Assisted …, 2015 | 111 | 2015 |
| Alternating Decision Forests S Schulter, P Wohlhart, C Leistner, A Saffari, PM Roth, H Bischof IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013, 2013 | 81 | 2013 |
| Conditioned regression models for non-blind single image super-resolution G Riegler, S Schulter, M Ruther, H Bischof Proceedings of the IEEE International Conference on Computer Vision, 522-530, 2015 | 78 | 2015 |
| Learning to simulate N Ruiz, S Schulter, M Chandraker arXiv preprint arXiv:1810.02513, 2018 | 77 | 2018 |
| Alternating regression forests for object detection and pose estimation S Schulter, C Leistner, P Wohlhart, PM Roth, H Bischof Proceedings of the IEEE International Conference on Computer Vision, 417-424, 2013 | 61 | 2013 |
| Learning to look around objects for top-view representations of outdoor scenes S Schulter, M Zhai, N Jacobs, M Chandraker Proceedings of the European Conference on Computer Vision (ECCV), 787-802, 2018 | 51 | 2018 |
| Accurate Object Detection with Joint Classification-Regression Random Forests S Schulter, C Leistner, P Wohlhart, PM Roth, H Bischof IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014, 2014 | 49 | 2014 |
| Domain adaptive semantic segmentation using weak labels S Paul, YH Tsai, S Schulter, AK Roy-Chowdhury, M Chandraker European conference on computer vision, 571-587, 2020 | 45 | 2020 |
| On-line Hough Forests S Schulter, C Leistner, PM Roth, L Van Gool, H Bischof British Machine Vision Conference, 2011 | 45 | 2011 |
| Shuffle and attend: Video domain adaptation J Choi, G Sharma, S Schulter, JB Huang European Conference on Computer Vision, 678-695, 2020 | 41 | 2020 |
| Improving classifiers with unlabeled weakly-related videos C Leistner, M Godec, S Schulter, A Saffari, M Werlberger, H Bischof CVPR 2011, 2753-2760, 2011 | 40 | 2011 |
| Interactive 3D segmentation of rock-art by enhanced depth maps and gradient preserving regularization M Zeppelzauer, G Poier, M Seidl, C Reinbacher, S Schulter, ... Journal on Computing and Cultural Heritage (JOCCH) 9 (4), 1-30, 2016 | 39 | 2016 |
| Hybrid one-shot 3d hand pose estimation by exploiting uncertainties G Poier, K Roditakis, S Schulter, D Michel, H Bischof, AA Argyros arXiv preprint arXiv:1510.08039, 2015 | 37 | 2015 |
| A parametric top-view representation of complex road scenes Z Wang, B Liu, S Schulter, M Chandraker Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 31 | 2019 |
| Object detection with a unified label space from multiple datasets X Zhao, S Schulter, G Sharma, YH Tsai, M Chandraker, Y Wu European Conference on Computer Vision, 178-193, 2020 | 24 | 2020 |
| Discriminative Hough Forests for Object Detection. P Wohlhart, S Schulter, M Köstinger, PM Roth, H Bischof BMVC, 1-11, 2012 | 24 | 2012 |
Manmohan ChandrakerUniversity of California, San DiegoVerified email at eng.ucsd.edu
