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Samuel Schulter
Samuel Schulter
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Title
Cited by
Cited by
Year
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
16762018
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
7502015
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
3712019
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
2442017
You should use regression to detect cells
P Kainz, M Urschler, S Schulter, P Wohlhart, V Lepetit
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th …, 2015
1432015
Learning to simulate
N Ruiz, S Schulter, M Chandraker
arXiv preprint arXiv:1810.02513, 2018
1352018
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
1092015
Shuffle and attend: Video domain adaptation
J Choi, G Sharma, S Schulter, JB Huang
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
1022020
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
912018
Domain adaptive semantic segmentation using weak labels
S Paul, YH Tsai, S Schulter, AK Roy-Chowdhury, M Chandraker
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
902020
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
832013
Exploiting unlabeled data with vision and language models for object detection
S Zhao, Z Zhang, S Schulter, L Zhao, BG Vijay Kumar, A Stathopoulos, ...
European conference on computer vision, 159-175, 2022
732022
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
662013
Object detection with a unified label space from multiple datasets
X Zhao, S Schulter, G Sharma, YH Tsai, M Chandraker, Y Wu
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
602020
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
552016
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
542014
Mm-tta: multi-modal test-time adaptation for 3d semantic segmentation
I Shin, YH Tsai, B Zhuang, S Schulter, B Liu, S Garg, IS Kweon, KJ Yoon
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
512022
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
452019
On-line Hough Forests
S Schulter, C Leistner, PM Roth, L Van Gool, H Bischof
British Machine Vision Conference, 2011
452011
Improving classifiers with unlabeled weakly-related videos
C Leistner, M Godec, S Schulter, A Saffari, M Werlberger, H Bischof
CVPR 2011, 2753-2760, 2011
432011
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Articles 1–20