Universal Adversarial Attacks for Visual Odometry Systems-Reference-Cited by-同舟云学术

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Universal Adversarial Attacks for Visual Odometry Systems

Published:2023-11-09 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Development and Learning (ICDL)
language:
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Author:

Xie Xijin¹,Liao Longlong¹,Yu Yuanlong¹,Guo Di²,Liu Huaping³

Affiliation:

1. College of Computer and Data Science, Fuzhou University,Fuzhou,China,350108

2. School of Artificial Intelligence, Beijing University of Posts and Telecommunications,Beijing,China

3. Tsinghua University,Department of Computer Science and Technology,Beijing,China,100084

Funder

Natural Science Foundation of Fujian Province of China

Program of National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10364334/10364349/10364418.pdf?arnumber=10364418

Reference34 articles.

1. DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks

2. Digging Into Self-Supervised Monocular Depth Estimation

3. Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

4. CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth Prediction

5. Intriguing properties of neural networks;Szegedy;arXiv preprint,2013

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