フォロー
Timo Rehfeld (Scharwächter)
Timo Rehfeld (Scharwächter)
Mercedes-Benz Research & Development North America
確認したメール アドレス: daimler.com
タイトル
引用先
引用先
The cityscapes dataset for semantic urban scene understanding
M Cordts, M Omran, S Ramos, T Rehfeld, M Enzweiler, R Benenson, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2016
89772016
The cityscapes dataset
M Cordts, M Omran, S Ramos, T Scharwächter, M Enzweiler, R Benenson, ...
CVPR Workshop on the Future of Datasets in Vision 2, 2015
2682015
Efficient multi-cue scene segmentation
T Scharwächter, M Enzweiler, U Franke, S Roth
Pattern Recognition: 35th German Conference, GCPR 2013, Saarbrücken, Germany …, 2013
1162013
Semantic stixels: Depth is not enough
L Schneider, M Cordts, T Rehfeld, D Pfeiffer, M Enzweiler, U Franke, ...
2016 IEEE Intelligent Vehicles Symposium (IV), 110-117, 2016
972016
Stixmantics: A medium-level model for real-time semantic scene understanding
T Scharwächter, M Enzweiler, U Franke, S Roth
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
732014
The stixel world: A medium-level representation of traffic scenes
M Cordts, T Rehfeld, L Schneider, D Pfeiffer, M Enzweiler, S Roth, ...
Image and Vision Computing 68, 40-52, 2017
462017
Low-level fusion of color, texture and depth for robust road scene understanding
T Scharwächter, U Franke
2015 IEEE Intelligent Vehicles Symposium (IV), 599-604, 2015
382015
Fully convolutional neural networks for dynamic object detection in grid maps
F Piewak, T Rehfeld, M Weber, JM Zöllner
2017 IEEE Intelligent Vehicles Symposium (IV), 392-398, 2017
232017
Visual guard rail detection for advanced highway assistance systems
T Scharwächter, M Schuler, U Franke
2014 IEEE Intelligent Vehicles Symposium Proceedings, 900-905, 2014
212014
A real-time multi-cue framework for determining optical flow confidence
SK Gehrig, T Scharwächter
2011 IEEE International Conference on Computer Vision Workshops (ICCV …, 2011
182011
Tree-structured models for efficient multi-cue scene labeling
M Cordts, T Rehfeld, M Enzweiler, U Franke, S Roth
IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (7), 1444-1454, 2016
142016
Environment estimation with dynamic grid maps and self-localizing tracklets
A Vatavu, N Rexin, S Appel, T Berling, S Govindachar, G Krehl, J Peukert, ...
2018 21st International Conference on Intelligent Transportation Systems …, 2018
82018
Estimating high definition map parameters with convolutional neural networks
S Bittel, T Rehfeld, M Weber, JM Zöllner
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 52-56, 2017
82017
Holistic grid fusion based stop line estimation
R Xu, F Tafazzoli, L Zhang, T Rehfeld, G Krehl, A Seal
2020 25th International Conference on Pattern Recognition (ICPR), 8400-8407, 2021
72021
Spider-based Stixel object segmentation
F Erbs, A Witte, T Scharwaechter, R Mester, U Franke
2014 IEEE Intelligent Vehicles Symposium Proceedings, 906-911, 2014
62014
Sensor fusion-based online map validation for autonomous driving
SR Bhavsar, A Vatavu, T Rehfeld, G Krehl
2020 IEEE Intelligent Vehicles Symposium (IV), 77-82, 2020
42020
Hierarchical Road Topology Learning for Urban Mapless Driving
L Zhang, F Tafazzoli, G Krehl, R Xu, T Rehfeld, M Schier, A Seal
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
32022
Stixel-Based Target Existence Estimation under Adverse Conditions
T Scharwächter
Pattern Recognition: 35th German Conference, GCPR 2013, Saarbrücken, Germany …, 2013
22013
Combining Appearance, Depth and Motion for Efficient Semantic Scene Understanding
T Rehfeld
Technische Universität, 2018
2018
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論文 1–19