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Fully Convolutional Neural Networks for Dynamic Object Detection in Grid
  Maps

Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps

10 September 2017
Florian Piewak
Timo Rehfeld
Michael Weber
Johann Marius Zöllner
    ObjD
ArXivPDFHTML

Papers citing "Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps"

4 / 4 papers shown
Title
A Random Finite Set Approach for Dynamic Occupancy Grid Maps with
  Real-Time Application
A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application
Dominik Nuss
Stephan Reuter
Markus Thom
Ting Yuan
Gunther Krehl
M. Maile
Axel Gern
Klaus C. J. Dietmayer
77
150
0
09 May 2016
Conditional Random Fields as Recurrent Neural Networks
Conditional Random Fields as Recurrent Neural Networks
Shuai Zheng
Sadeep Jayasumana
Bernardino Romera-Paredes
Vibhav Vineet
Zhizhong Su
Dalong Du
Chang Huang
Philip Torr
SSeg
234
2,536
0
11 Feb 2015
Semantic Image Segmentation with Deep Convolutional Nets and Fully
  Connected CRFs
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Liang-Chieh Chen
George Papandreou
Iasonas Kokkinos
Kevin Patrick Murphy
Alan Yuille
SSeg
176
4,892
0
22 Dec 2014
Caffe: Convolutional Architecture for Fast Feature Embedding
Caffe: Convolutional Architecture for Fast Feature Embedding
Yangqing Jia
Evan Shelhamer
Jeff Donahue
Sergey Karayev
Jonathan Long
Ross B. Girshick
S. Guadarrama
Trevor Darrell
VLM
BDL
3DV
271
14,707
0
20 Jun 2014
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