Probabilistic Object Detection: Definition and Evaluation

Probabilistic Object Detection: Definition and Evaluation

27 November 2018

Niko Sünderhauf

Papers citing "Probabilistic Object Detection: Definition and Evaluation"

14 / 64 papers shown

Title
Multi-Agent Active Search using Realistic Depth-Aware Noise Model Ramina Ghods W. Durkin J. Schneider 16 14 0 09 Nov 2020
The Robotic Vision Scene Understanding Challenge David Hall Ben Talbot S. Bista Haoyang Zhang Rohan Smith Feras Dayoub Niko Sünderhauf 21 13 0 11 Sep 2020
Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts Tiago Azevedo R. D. Jong Matthew Mattina Partha P. Maji UQCV 8 15 0 07 Sep 2020
Probabilistic Deep Learning for Instance Segmentation J. L. Rumberger Lisa Mais Dagmar Kainmueller UQCV SSeg 8 9 0 24 Aug 2020
Representation Learning with Video Deep InfoMax R. Devon Hjelm Philip Bachman SSL MDE 16 28 0 27 Jul 2020
Inferring Spatial Uncertainty in Object Detection Zining Wang Di Feng Yiyang Zhou Lars Rosenbaum Fabian Timm Klaus C. J. Dietmayer M. Tomizuka Wei Zhan 16 27 0 07 Mar 2020
MonoLayout: Amodal scene layout from a single image Kaustubh Mani Swapnil Daga Shubhika Garg N. S. Shankar Krishna Murthy Jatavallabhula K. M. Krishna 6 79 0 19 Feb 2020
Empirical Upper Bound in Object Detection and More Ali Borji Seyed Mehdi Iranmanesh VLM ObjD 14 24 0 27 Nov 2019
SMArT: Training Shallow Memory-aware Transformers for Robotic Explainability Marcella Cornia Lorenzo Baraldi Rita Cucchiara 6 27 0 07 Oct 2019
The Probabilistic Object Detection Challenge John Skinner David Hall Haoyang Zhang Feras Dayoub Niko Sünderhauf AAML 6 9 0 19 Mar 2019
BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors Ali Harakeh Michael H. W. Smart Steven L. Waslander BDL UQCV 18 115 0 09 Mar 2019
Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges Di Feng Christian Haase-Schuetz Lars Rosenbaum Heinz Hertlein Claudius Gläser Fabian Duffhauss W. Wiesbeck Klaus C. J. Dietmayer 3DPC 27 985 0 21 Feb 2019
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 197 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015