• Corpus ID: 60440409

NeurAll: Towards a Unified Model for Visual Perception in Automated Driving

@article{Sistu2019NeurAllTA,
  title={NeurAll: Towards a Unified Model for Visual Perception in Automated Driving},
  author={Ganesh Sistu and Isabelle Leang and Sumanth Chennupati and Stefan Milz and Senthil Kumar Yogamani and Samir A. Rawashdeh},
  journal={ArXiv},
  year={2019},
  volume={abs/1902.03589}
}
Convolutional Neural Networks (CNNs) are successfully used for the important automotive visual perception tasks including object recognition, motion and depth estimation, visual SLAM, etc. However, these tasks are typically independently explored and modeled. In this paper, we propose a joint multi-task network design for learning several tasks simultaneously. Our main motivation is the computational efficiency achieved by sharing the expensive initial convolutional layers between all tasks… 

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