Samuel Schulter

Senior Research Scientist
Amazon
New York, NY


I'm a research scientist at Amazon in New York City, NY. Before that I was a researcher in the Media-Analytics Department at NEC Laboratories America, Inc in San Jose, CA, working with Manmohan Chandraker. My research interests are in computer vision and machine learning. I received my PhD from Graz University of Technology under the supervision of Horst Bischof.


☃ Publications

[Google Scholar]
Object Detection with a Unified Label Space from Multiple Datasets
Xiangyun Zhao, Samuel Schulter, Gaurav Sharma, Yi-Hsuan Tsai, Manmohan Chandraker, Ying Wu
ECCV 2020 [pdf, supp, dataset]
Domain Adaptive Semantic Segmentation Using Weak Labels
Sujoy Paul, Yi-Hsuan Tsai, Samuel Schulter, Amit K. Roy-Chowdhury, Manmohan Chandraker
ECCV 2020 [pdf, project]
Shuffle and Attend: Video Domain Adaptation
Jinwoo Choi, Gaurav Sharma, Samuel Schulter, Jia-Bin Huang
ECCV 2020 [pdf]
Peek-a-Boo: Occlusion Reasoning in Indoor Scenes With Plane Representations
Ziyu Jiang, Buyu Liu, Samuel Schulter, Zhangyang Wang, Manmohan Chandraker
CVPR 2020 [pdf, supp]
Understanding Road Layout From Videos as a Whole
Buyu Liu, Bingbing Zhuang, Samuel Schulter, Pan Ji, Manmohan Chandraker
CVPR 2020 [pdf, supp]
Domain Adaptation for Structured Output via Discriminative Patch Representations
Yi-Hsuan Tsai, Kihyuk Sohn, Samuel Schulter, Manmohan Chandraker
ICCV 2019 [pdf, supp]
A Parametric Top-View Representation of Complex Road Scenes
Ziyan Wang, Buyu Liu, Samuel Schulter, Manmohan Chandraker
CVPR 2019 [pdf, supp]
A Dataset for High-Level 3D Scene Understanding of Complex Road Scenes in the Top-View
Ziyan Wang, Buyu Liu, Samuel Schulter, Manmohan Chandraker
CVPR 2019 Workshop on 3D Scene Understanding for Vision, Graphics, and Robotics. [pdf, project]
Learning to Simulate
Nataniel Ruiz, Samuel Schulter, Manmohan Chandraker
ICLR 2019 [pdf, poster, openreview, medium post]
Memory Warps for Learning Long-Term Online Video Representations
Tuan-Hung Vu, Wongun Choi, Samuel Schulter, Manmohan Chandraker
WACV 2019 [pdf]
Learning to Look around Objects for Top-View Representations of Outdoor Scenes
Samuel Schulter, Menghua Zhai, Nathan Jacobs, Manmohan Chandraker
ECCV 2018 [pdf]
Learning to Adapt Structured Output Space for Semantic Segmentation
Yi-Hsuan Tsai, Wei-Chih Hung, Samuel Schulter, Kihyuk Sohn, Ming-Hsuan Yang, Manmohan Chandraker
CVPR 2018 [pdf, supp, code]
Deep Network Flow for Multi-Object Tracking
Samuel Schulter, Paul Vernaza, Wongun Choi, Manmohan Chandraker
CVPR 2017 [pdf, supp]
Loss-Specific Training of Random Forests for Super-Resolution
Alexander Grabner, Georg Poier, Michael Opitz, Samuel Schulter, Peter M. Roth
Computer Vision Winter Workshop 2017 [pdf]
Interactive 3D Segmentation of Rock-Art by Enhanced Depth Maps and Gradient Preserving Regularization
Matthias Zeppelzauer, Georg Poier, Markus Seidl, Christian Reinbacher, Samuel Schulter, Christian Breiteneder, Horst Bischof
ACM Journal on Computing and Cultural Heritage 9 (4): 19:1-19:30, 2016 [pdf]
Conditioned Regression Models for Non-Blind Single Image Super-Resolution
Gernot Riegler, Samuel Schulter, Matthias Ruether, Horst Bischof
ICCV 2015 [pdf]
Hybrid One-Shot 3D Hand Pose Estimation by Exploiting Uncertainties
Georg Poier, Konstantinos Roditakis, Samuel Schulter, Damien Michel, Horst Bischof Antonis A. Argyros
BMVC 2015 [pdf, project]
Interactive Segmentation of Rock-Art in High-Resolution 3D Reconstructions
Matthias Zeppelzauer, Georg Poier, Markus Seidl, Christian Reinbacher, Christian Breiteneder, Horst Bischof, Samuel Schulter
Digital Heritage Conference 2015 [pdf]
You Should Use Regression to Detect Cells
Philipp Kainz, Martin Urschler, Samuel Schulter, Paul Wohlhart, Vincent Lepetit
MICCAI 2015 [pdf, code]
Fast and Accurate Super Resolution with Random Forests
Samuel Schulter, Christian Leistner, Horst Bischof
CVPR 2015 [pdf, supp, code]
Hough Forests Revisited: An Approach to Multiple Instance Tracking from Multiple Cameras
Georg Poier, Samuel Schulter, Sabine Sternig, Peter M. Roth, Horst Bischof
GCPR 2014 [pdf]
Accurate Object Detection with Joint Classification-Regression Random Forests
Samuel Schulter, Christian Leistner, Paul Wohlhart, Peter M. Roth, Horst Bischof
CVPR 2014 [pdf]
Alternating Regression Forests for Object Detection and Pose Estimation
Samuel Schulter, Christian Leistner, Paul Wohlhart, Peter M. Roth, Horst Bischof
ICCV 2013 [pdf, code]
Unsupervised Object Discovery and Segmentation in Videos
Samuel Schulter, Christian Leistner, Peter M. Roth, Horst Bischof
BMVC 2013 [pdf]
Ordinal Random Forests for Object Detection
Samuel Schulter, Peter M. Roth, Horst Bischof
GCPR 2013 [pdf]
Alternating Decision Forests
Samuel Schulter, Paul Wohlhart, Christian Leistner, Amir Saffari, Peter M. Roth, Horst Bischof
CVPR 2013 [pdf, code]
Discriminative Hough Forests for Object Detection
Paul Wohlhart, Samuel Schulter, Martin Koestinger, Peter M. Roth, Horst Bischof
BMVC 2012 [pdf]
Improving Classifiers with Unlabeled Weakly-Related Videos
Christian Leistner, Martin Godec, Samuel Schulter, Amir Saffari, Manuel Werlberger, Horst Bischof
CVPR 2011 [pdf, code]
On-line Hough Forests
Samuel Schulter, Christian Leistner, Peter M. Roth, Luc Van Gool, Horst Bischof
BMVC 2011 [pdf, code]