@inproceedings{72031bf375694c8b817394458f18c918,
title = "Detection and Depth Estimation for Objects from Single Monocular Image",
abstract = "This paper addresses the problem of detecting and estimating depth for objects given a single monocular RGB image. We propose a integrative network to implement multiple tasks of detection and depth estimation at the same time and realize the rate of 6 fps. We use convolutional neural network to extract features and fully connection network to generate depth straightway and evaluate the performance of our model on KITTY. To adapt the model to multiple range scales of objects, we rectify the loss function and further improve the performance of our model.",
keywords = "Depth estimation, Monocular vision, Object detection",
author = "Ziwen Xu and Yingmin Jia",
note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; Chinese Intelligent Systems Conference, CISC 2020 ; Conference date: 24-10-2020 Through 25-10-2020",
year = "2021",
doi = "10.1007/978-981-15-8450-3\_4",
language = "英语",
isbn = "9789811584497",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "27--35",
editor = "Yingmin Jia and Weicun Zhang and Yongling Fu",
booktitle = "Proceedings of 2020 Chinese Intelligent Systems Conference - Volume I",
address = "德国",
}