Learning Collision-Free Space Detection from Stereo Images: Homography Matrix Brings Better Data Augmentation

@article{Fan2020LearningCS,
  title={Learning Collision-Free Space Detection from Stereo Images: Homography Matrix Brings Better Data Augmentation},
  author={Rui Fan and Hengli Wang and Peide Cai and Jin Wu and M. J. Bocus and Lei Qiao and Ming Liu},
  journal={ArXiv},
  year={2020},
  volume={abs/2012.07890}
}
Collision-free space detection is a critical component of autonomous vehicle perception. The state-of-the-art algorithms are typically based on supervised deep learning. Their performance is dependent on the quality and amount of labeled training data. It remains an open challenge to train deep convolutional neural networks (DCNNs) using only a small quantity of training samples. Therefore, in this paper, we mainly explore an effective training data augmentation approach that can be employed to… Expand
7 Citations

Figures and Tables from this paper

Computer Stereo Vision for Autonomous Driving
  • 6
  • PDF
Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms
  • 6
  • PDF
End-to-End Interactive Prediction and Planning with Optical Flow Distillation for Autonomous Driving
  • PDF
Learning Interpretable End-to-End Vision-Based Motion Planning for Autonomous Driving with Optical Flow Distillation
  • Hengli Wang, Peide Cai, Yuxiang Sun, Lujia Wang, Ming Liu
  • Computer Science
  • ArXiv
  • 2021
  • 2
  • PDF
PVStereo: Pyramid Voting Module for End-to-End Self-Supervised Stereo Matching
  • 2
  • PDF
S2P2: Self-Supervised Goal-Directed Path Planning Using RGB-D Data for Robotic Wheelchairs
  • Hengli Wang, Yuxiang Sun, Rui Fan, Ming Liu
  • Computer Science
  • ArXiv
  • 2021
  • 2
  • PDF

References

SHOWING 1-10 OF 57 REFERENCES
SNE-RoadSeg: Incorporating Surface Normal Information into Semantic Segmentation for Accurate Freespace Detection
  • 18
  • PDF
Pyramid Stereo Matching Network
  • Jia-Ren Chang, Y. Chen
  • Computer Science
  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  • 2018
  • 490
  • PDF
3D Object Proposals for Accurate Object Class Detection
  • 466
  • PDF
A new performance measure and evaluation benchmark for road detection algorithms
  • 419
  • Highly Influential
  • PDF
Road estimation with sparse 3D points from stereo data
  • 22
Semantic segmentation of terrain and road terrain for advanced driver assistance systems
  • 6
  • PDF
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
  • 6,755
  • PDF
DenseASPP for Semantic Segmentation in Street Scenes
  • 403
  • Highly Influential
  • PDF
...
1
2
3
4
5
...