Traffic-Sign Detection and Classification in the Wild
Tsinghua University · Lehigh University · +1 more institution
Abstract
Although promising results have been achieved in the areas of traffic-sign detection and classification, few works have provided simultaneous solutions to these two tasks for realistic real world images. We make two contributions to this problem. Firstly, we have created a large traffic-sign benchmark from 100000 Tencent Street View panoramas, going beyond previous benchmarks. It provides 100000 images containing 30000 traffic-sign instances. These images cover large variations in illuminance and weather conditions. Each traffic-sign in the benchmark is annotated with a class label, its bounding box and pixel mask. We call this benchmark Tsinghua-Tencent 100K. Secondly, we demonstrate how a robust end-to-end…
Citation impact
- FWCI
- 28.72
- Percentile
- 100%
- References
- 39
Authors
6Topics & keywords
- Computer science
- Benchmark (surveying)
- Convolutional neural network
- Robustness (evolution)
- Traffic sign
- Minimum bounding box
- Artificial intelligence
- Bounding overwatch
- Sustainable cities and communities