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Modern computer vision algorithms typically require expensive data acquisition and accurate manual labeling.
Inferring 3d structure with a statistical image-based shape model
Kristen Grauman, Gregory Shakhnarovich, and Trevor Darrell · 2003
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Model-based validation approaches and matching techniques for automotive vision based pedestrian detection
A. Broggi, A. Fascioli, P. Grisleri, T. Graf, and M. Meinecke · 2005
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Ovvv: Using virtual worlds to design and evaluate surveillance systems
Geoffrey R Taylor, Andrew J Chosak, and Paul C Brewer · 2007
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Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics
Keni Bernardin and Rainer Stiefelhagen · 2008
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Differences between stereo and motion behaviour on synthetic and real-world stereo sequences
Tobi Vaudrey, Clemens Rabe, Reinhard Klette, and James Milburn · 2008
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Global data association for multi-object tracking using network flows
Li Zhang, Yuan Li, and Ramakant Nevatia · 2008
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Back to the future: Learning shape models from 3d cad data
Michael Stark, Michael Goesele, and Bernt Schiele · 2010
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Learning appearance in virtual scenarios for pedestrian detection
J. Marin, D. Vazquez, D. Geronimo, and A.M. Lopez · 2010
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Evaluation of image features using a photorealistic virtual world
B. Kaneva, A. Torralba, and W.T. Freeman · 2011
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Online Multi-Person Tracking-by-Detection from a Single, Uncalibrated Camera
MD Breitenstein, F Reichlin, B Leibe, E Koller-Meier, and L Van Gool · 2011
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Globally-optimal greedy algorithms for tracking a variable number of objects
H Pirsiavash, D Ramanan, and C Fowlkes · 2011
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Are we ready for autonomous driving? The KITTI vision benchmark suite
A Geiger, P Lenz, and R Urtasun · 2012
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Teaching 3d geometry to deformable part models
Bojan Pepik, Michael Stark, Peter Gehler, and Bernt Schiele · 2012
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Data-driven scene understanding from 3d models
Scott Satkin, Jason Lin, and Martial Hebert · 2012
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A naturalistic open source movie for optical flow evaluation
D. J. Butler, J. Wulff, G. B. Stanley, and M. J. Black · 2012
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Motion capture of hands in action using discriminative salient points
Luca Ballan, Aparna Taneja, Jürgen Gall, Luc Van Gool, and Marc Pollefeys · 2012
Cited alongside, same era.
Unsupervised domain adaptation of virtual and real worlds for pedestrian detection
D. Vázquez, A.M. López, and D. Ponsa · 2012
Cited alongside, same era.
A naturalistic open source movie for optical flow evaluation
Daniel J. Butler, Jonas Wulff, Garrett B. Stanley, and Michael J. Black · 2012
Cited alongside, same era.
A kernel two-sample test
A Gretton, KM Borgwardt, MJ Rasch, B Schölkopf, and A Smola · 2012
Cited alongside, same era.
Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures
Hybrid Stochastic/Deterministic Optimization for Tracking Sports Players and Pedestrians
RT Collins and P Carr · 2014
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Multiple object tracking: A review
W Luo, X Zhao, and TK Kim · 2014
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Edge Boxes: Locating Object Proposals from Edges
CL Zitnick and P Dollar · 2014
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Fast R-CNN
R Girshick · 2015
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Picture: A Probabilistic Programming Language for Scene Perception
TD Kulkarni, P Kohli, JB Tenenbaum, and V Mansinghka · 2015
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Learning scene-specific pedestrian detectors without real data
Hiro Hattori, Vishnu Bodetti, Kris M. Kitani, and Takeo Kanade · 2015
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J Bergstra, D Yamins, and D Cox · 2013
Cited alongside, same era.
Simulation as an engine of physical scene understanding
Peter W Battaglia, Jessica B Hamrick, and Joshua B Tenenbaum · 2013
Cited alongside, same era.
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
V Mansinghka, TD Kulkarni, YN Perov, and J Tenenbaum · 2013
Cited alongside, same era.
Virtual and real world adaptation for pedestrian detection
D. Vazquez, A. Lopez, J. Marin, D. Ponsa, and D. Geronimo · 2014
Cited alongside, same era.
Seeing 3D chairs: exemplar part-based 2D-3D alignment using a large dataset of CAD models
M Aubry, D Maturana, A Efros, B Russell, and J Sivic · 2014
Cited alongside, same era.
From Virtual to Reality: Fast Adaptation of Virtual Object Detectors to Real Domains
B Sun and K Saenko · 2014
Cited alongside, same era.
Continuous Energy Minimization for Multi-Target Tracking
A Milan, S Roth, and K Schindler · 2014
Cited alongside, same era.
Adaptation of Synthetic Data for Coarse-to-Fine Viewpoint Refinement
PP Busto, J Liebelt, and J Gall · 2015
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Learning Deep Object Detectors from 3D Models
X Peng, B Sun, K Ali, and K Saenko · 2015
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DeepDriving: Learning affordance for direct perception in autonomous driving
Chenyi Chen, Ari Seff, Alain L. Kornhauser, and Jianxiong Xiao · 2015
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Online Domain Adaptation for Multi-Object Tracking
A Gaidon and E Vig · 2015
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Learning Optimal Parameters For Multi-target Tracking
Shaofei Wang and C Fowlkes · 2015
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Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor
Wongun Choi · 2015
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Learning to Track : Online Multi-Object Tracking by Decision Making
Yu Xiang, A Alahi, and S Savarese · 2015
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A Geiger, P Lenz, and R Urtasun · 2016
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