GEM: Glare or Gloom, I Can Still See You – End-to-End Multi-Modal Object Detection

@article{Mazhar2021GEMGO,
  title={GEM: Glare or Gloom, I Can Still See You – End-to-End Multi-Modal Object Detection},
  author={Osama Mazhar and Robert Babu{\vs}ka and Jens Kober},
  journal={IEEE Robotics and Automation Letters},
  year={2021},
  volume={6},
  pages={6321-6328}
}
Deep neural networks designed for vision tasks are often prone to failure when they encounter environmental conditions not covered by the training data. Single-modal strategies are insufficient when the sensor fails to acquire information due to malfunction or its design limitations. Multi-sensor configurations are known to provide redundancy, increase reliability, and are crucial in achieving robustness against asymmetric sensor failures. To address the issue of changing lighting conditions… Expand

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