ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1809.03782
  4. Cited By
Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks

Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks

11 September 2018
M. Schreiber
S. Hörmann
Klaus C. J. Dietmayer
ArXivPDFHTML

Papers citing "Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks"

17 / 17 papers shown
Title
Self-supervised Multi-future Occupancy Forecasting for Autonomous Driving
Self-supervised Multi-future Occupancy Forecasting for Autonomous Driving
Bernard Lange
Masha Itkina
Jiachen Li
Mykel J. Kochenderfer
74
4
0
30 Jul 2024
Offline Object Extraction from Dynamic Occupancy Grid Map Sequences
Offline Object Extraction from Dynamic Occupancy Grid Map Sequences
Daniel Stumper
Fabian Gies
S. Hörmann
Klaus C. J. Dietmayer
58
9
0
11 Apr 2018
Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM
  Encoder-Decoder Architecture
Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture
Seonghyeon Park
Byeongdo Kim
C. Kang
C. Chung
J. Choi
54
409
0
18 Feb 2018
Dynamic Occupancy Grid Prediction for Urban Autonomous Driving: A Deep
  Learning Approach with Fully Automatic Labeling
Dynamic Occupancy Grid Prediction for Urban Autonomous Driving: A Deep Learning Approach with Fully Automatic Labeling
Stefan Hoermann
Martin Bach
Klaus C. J. Dietmayer
63
165
0
24 May 2017
Fully Convolutional Networks for Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer
Jonathan Long
Trevor Darrell
VOS
SSeg
735
37,846
0
20 May 2016
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
79
150
0
09 May 2016
End-to-End Tracking and Semantic Segmentation Using Recurrent Neural
  Networks
End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks
Peter Ondruska
J. Dequaire
Dominic Zeng Wang
Ingmar Posner
87
62
0
18 Apr 2016
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks
Peter Ondruska
Ingmar Posner
55
239
0
02 Feb 2016
Convolutional LSTM Network: A Machine Learning Approach for
  Precipitation Nowcasting
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian Shi
Zhourong Chen
Hao Wang
Dit-Yan Yeung
W. Wong
W. Woo
551
7,989
0
13 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
1.8K
77,133
0
18 May 2015
Learning Deconvolution Network for Semantic Segmentation
Learning Deconvolution Network for Semantic Segmentation
Hyeonwoo Noh
Seunghoon Hong
Bohyung Han
SSeg
232
4,177
0
17 May 2015
Unsupervised Learning of Video Representations using LSTMs
Unsupervised Learning of Video Representations using LSTMs
Nitish Srivastava
Elman Mansimov
Ruslan Salakhutdinov
SSL
130
2,590
0
16 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,039
0
22 Dec 2014
Sequence to Sequence Learning with Neural Networks
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever
Oriol Vinyals
Quoc V. Le
AIMat
434
20,541
0
10 Sep 2014
Recurrent Neural Network Regularization
Recurrent Neural Network Regularization
Wojciech Zaremba
Ilya Sutskever
Oriol Vinyals
ODL
137
2,776
0
08 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.6K
100,348
0
04 Sep 2014
On the difficulty of training Recurrent Neural Networks
On the difficulty of training Recurrent Neural Networks
Razvan Pascanu
Tomas Mikolov
Yoshua Bengio
ODL
190
5,342
0
21 Nov 2012
1