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When incorporating deep neural networks into robotic systems, a major challenge is the lack of uncertainty measures associated with their output predictions.
Probable networks and plausible predictions—a review of practical bayesian methods for supervised neural networks
David JC MacKay · 1995
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Bayesian data analysis
Andrew Gelman, Hal S Stern, John B Carlin, David B Dunson, Aki Vehtari, and Donald B Rubin · 2013
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Suspicious object detection in surveillance videos for security applications
Trupti M Pandit, PM Jadhav, and AC Phadke · 2016
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2016
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Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
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What uncertainties do we need in bayesian deep learning for computer vision?
Alex Kendall and Yarin Gal · 2017
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Speed/accuracy trade-offs for modern convolutional object detectors
Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, and Kevin Murphy · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollar · 2017
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Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
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Joint 3d proposal generation and object detection from view aggregation
Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, and Steven Waslander · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Towards safe autonomous driving: Capture uncertainty in the deep neural network for lidar 3d vehicle detection
Di Feng, Lars Rosenbaum, and Klaus Dietmayer · 2018
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Leveraging heteroscedastic aleatoric uncertainties for robust real-time lidar 3d object detection
Di Feng, Lars Rosenbaum, and Klaus Dietmayer · 2018
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Uncertainty estimation for deep neural object detectors in safety-critical applications
Michael Truong Le, Frederik Diehl, Thomas Brunner, and Alois Knol · 2018
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Bdd100k: A diverse driving video database with scalable annotation tooling
Fisher Yu, Wenqi Xian, Yingying Chen, Fangchen Liu, Mike Liao, Vashisht Madhavan, and Trevor Darrell · 2018
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Evidential deep learning to quantify classification uncertainty
Murat Sensoy, Lance Kaplan, and Melih Kandemir · 2018
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Yin Zhou and Oncel Tuzel · 2018
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The limits and potentials of deep learning for robotics
Niko Sünderhauf, Oliver Brock, Walter Scheirer, Raia Hadsell, Dieter Fox, Jürgen Leitner, Ben Upcroft, Pieter Abbeel, Wolfram Burgard, Michael Milford, et al · 2018
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Dropout sampling for robust object detection in open-set conditions
Dimity Miller, Lachlan Nicholson, Feras Dayoub, and Niko Sünderhauf · 2018
Cited alongside, same era.
Evaluating merging strategies for sampling-based uncertainty techniques in object detection
Dimity Miller, Feras Dayoub, Michael Milford, and Niko Sünderhauf · 2018
Cited alongside, same era.
Probability-based detection quality (PDQ): A probabilistic approach to detection evaluation
David Hall, Feras Dayoub, John Skinner, Peter Corke, Gustavo Carneiro, and Niko Sünderhauf · 2018
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Lasernet: An efficient probabilistic 3d object detector for autonomous driving
Gregory P Meyer, Ankit Laddha, Eric Kee, Carlos Vallespi-Gonzalez, and Carl K Wellington · 2019
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Bounding box regression with uncertainty for accurate object detection
Yihui He, Chenchen Zhu, Jianren Wang, Marios Savvides, and Xiangyu Zhang · 2019
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Uncertainty estimation in one-stage object detection
Florian Kraus and Klaus Dietmayer · 2019
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