Multi-Modal Depth Estimation Using Convolutional Neural Networks

@article{Siddiqui2020MultiModalDE,
  title={Multi-Modal Depth Estimation Using Convolutional Neural Networks},
  author={Sadique Adnan Siddiqui and A. Vierling and K. Berns},
  journal={2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)},
  year={2020},
  pages={354-359}
}
This paper addresses the problem of dense depth predictions from sparse distance sensor data and a single camera image on challenging weather conditions. This work explores the significance of different sensor modalities such as camera, Radar, and Lidar for estimating depth by applying Deep Learning approaches. Although Lidar has higher depth-sensing abilities than Radar and has been integrated with camera images in lots of previous works, depth estimation using CNN's on the fusion of robust… Expand

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