journal article·2024Open access

A Real-Time Semantic Segmentation Method Based on Transformer for Autonomous Driving

Weiyu Hao, Jingyi Wang, Huimin Lu

Computers, Materials & Continua· Volume 81· Issue 3

Abstract

While traditional Convolutional Neural Network (CNN)-based semantic segmentation methods have proven effective, they often encounter significant computational challenges due to the requirement for dense pixel-level prediction... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Autonomous Vehicle Technology and Safety

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (17)

Show source-provided references
1. One-shot video object segmentation
2. Video segmentation by tracing discontinuities in a trajectory embedding
3. Fully convolutional networks for semantic segmentation
4. F. Yu and V. Koltun, “Multi-scale context aggregation by dilated convolutions,” 2015, arXiv:1511.07122.
5. U-Net: Convolutional networks for biomedical image segmentation
6. C. Chen, G. Papandreou, F. Schroff, and H. Adam, “Rethinking atrous convolution for semantic image segmentation,” 2017, arXiv:1706.05587.
7. Pyramid scene parsing network
8. SegNet: A deep convolutional encoder-decoder architecture for image segmentation10.1109/TPAMI.2016.2644615 ↗
9. A. Paszke, A. Chaurasia, S. Kim, and E. Culurciello, “ENet: A deep neural network architecture for real-time semantic segmentation,” 2016, arXiv:1606.02147.
10. Chowdhary · Fundamentals of Artificial Intelligence · 2020 · 603
11. Advances in natural language processing10.1126/science.aaa8685 ↗
12. End-to-end object detection with transformers
13. Z. Zheng et al., “Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers,” 2020, arXiv:2012.15840.10.1109/CVPR46437.2021.00681 ↗
14. Y. Yuan et al., “Tokens-to-Token ViT: Training vision transformers from scratch on imageNet,” 2021, arXiv:2101.11986.10.1109/ICCV48922.2021.00060 ↗
15. DWin-HRFormer: A high-resolution transformer model with directional windows for semantic segmentation of urban construction land
16. SegNeXt: Rethinking convolutional attention design for semantic segmentation
17. TopFormer: Topology-aware transformer for point cloud registration