Fetching the paper…
Reading the bibliography…
Environmental perception is an important aspect within the field of autonomous vehicles that provides crucial information about the driving domain, including but not limited to identifying clear driving areas and surrounding obstacles.
1903
Earlier work this paper cites.
1912
Earlier work this paper cites.
2004
Earlier work this paper cites.
KIM, ZuWhan. Robust lane detection and tracking in challenging scenarios. IEEE Transactions on intelligent transportation systems, 2008, vol. 9, no 1, p. 16-26
2008
Earlier work this paper cites.
Lin, T. Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., … & Zitnick, C. L. (2014, September). Microsoft coco: Common objects in context. In European conference on computer vision (pp. 740-755). Springer, Cham
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele, “The Cityscapes Dataset for Semantic Urban Scene Understanding,” 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 3213-3223, doi: 10.1109/CVPR.2016.350
2016
Earlier work this paper cites.
DUONG, Tin Trung, PHAM, Cuong Cao, TRAN, Tai Huu-Phuong, et al. Near real-time ego-lane detection in highway and urban streets. In : 2016 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia). IEEE, 2016. p. 1-4
2016
Earlier work this paper cites.
C. Yu, J. Wang, C. Peng, C. Gao, G. Yu, and N.Sang. (2018). Bisenet: Bilateral segmentation network for real-time semantic segmentation. In Proceedings of the European conference on computer vision (ECCV) (pp. 325-341)
2018
Earlier work this paper cites.
K. Min, S. Han, D. Lee, D. Choi, K. Sung and J. Choi, ”SAE Level 3 Autonomous Driving Technology of the ETRI,” 2019 International Conference on Information and Communication Technology Convergence (ICTC), 2019, pp. 464-466, doi: 10.1109/ICTC46691.2019.8939765
2019
Earlier work this paper cites.
M. Hua, Y. Nan and S. Lian, ”Small Obstacle Avoidance Based on RGB-D Semantic Segmentation,” 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019, pp. 886-894, doi: 10.1109/ICCVW.2019.00117
2019
Cited alongside, same era.
D. Bolya, C. Zhou, F. Xiao and Y. J. Lee, ”YOLACT: Real-Time Instance Segmentation,” 2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 9156-9165, doi: 10.1109/ICCV.2019.00925
2019
Cited alongside, same era.
P. Chao, C. -Y. Kao, Y. Ruan, C. -H. Huang and Y. -L. Lin, ”HarDNet: A Low Memory Traffic Network,” 2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 3551-3560, doi: 10.1109/ICCV.2019.00365
2019
Cited alongside, same era.
L. Bartolomei, L. Teixeira and M. Chli, ”Perception-aware Path Planning for UAVs using Semantic Segmentation,” 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020, pp. 5808-5815, doi: 10.1109/IROS45743.2020.9341347
2020
Technische Universität Braunschweig, ”Carolo-Master-Cup@Home Regulations 2021,” 20 Jan 2021. [Online]. Available: https://www.tu-braunschweig.de/fileadmin/Redaktionsgruppen/Institute_Fakultaet_5/Carolo-Cup/Basic-Cup_Regulations_210120.pdf . [Accessed February 2021]
2021
Later among the works it cites.
S. Cakir, M. Gauß, K. Häppeler, and Y. Ounajjar, Road generation to use in a simulation for semantic segmentation, Esslingen University of Applied Sciences. [Online]. Available: https://github.com/Sinop97/drive_sim_road_generation . [Accessed July 2021]
2021
Later among the works it cites.
Team Spatzenhirn, University of Ulm. [Online]. Available: https://www.uni-ulm.de/en/in/spatzenhirn/ . [Accessed July 2021]
2021
Later among the works it cites.
Team ISF Löwen, Institute of Software Engineering and Automotive Informatics, TU Braunschweig. [Online]. Available: http://www.isf-loewen.de/ . [Accessed July 2021]
2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
H. Kirchner, Randomized Road Generation and 3D Visualization, TU Munich. [Online]. Available: https://github.com/tum-phoenix/drive_sim_road_generation . [Accessed May 2020]
2020
Cited alongside, same era.
H. Chen, K. Sun, Z. Tian, C. Shen, Y. Huang and Y. Yan, ”BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation,” 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 8570-8578, doi: 10.1109/CVPR42600.2020.00860
2020
Cited alongside, same era.
D. Bolya, C. Zhou, F. Xiao and Y. J. Lee, ”YOLACT++ Better Real-Time Instance Segmentation,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 2, pp. 1108-1121, 1 Feb. 2022, doi: 10.1109/TPAMI.2020.3014297
2020
Cited alongside, same era.
Y. Lee and J. Park, ”CenterMask: Real-Time Anchor-Free Instance Segmentation,” 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 13903-13912, doi: 10.1109/CVPR42600.2020.01392
2020
Cited alongside, same era.
T. Nguyen and M. Yoo, ”Fusing LIDAR sensor and RGB camera for object detection in autonomous vehicle with fuzzy logic approach,” 2021 International Conference on Information Networking (ICOIN), 2021, pp. 788-791, doi: 10.1109/ICOIN50884.2021.9334015
2021
Cited alongside, same era.
Team KITcar, Karlsruhe Institute of Technology. [Online]. Available: https://kitcar-team.de/ . [Accessed July 2021]
2021
Later among the works it cites.
Team it:movES, Esslingen University of Applied Sciences. [Online]. Available: https://www.hs-esslingen.de/informatik-und-informationstechnik/forschung-labore/projekte/interne-projekte/ . [Accessed July 2021]
2021
Later among the works it cites.
Papers with code, “HarDNet: A Low Memory Traffic Network,” Accessed: Jul 01, 2021. [Online]. Available: https://paperswithcode.com/paper/hardnet-a-low-memory-traffic-network
2021
Later among the works it cites.
S. Cakir, M. Gauß, K. Häppeler, and Y. Ounajjar, How to train FasterSeg for custom objects, Esslingen University of Applied Sciences. [Online]. Available: https://github.com/Gaussianer/FasterSeg . [Accessed July 2021]
2021
Later among the works it cites.
S. Minaee, Y. Y. Boykov, F. Porikli, A. J. Plaza, N. Kehtarnavaz and D. Terzopoulos, ”Image Segmentation Using Deep Learning: A Survey,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2021.3059968
2021
Later among the works it cites.