Bo Liu

Orcid: 0000-0002-3164-6299

Affiliations:
  • Chongqing University of Posts and Telecommunications, Department of Computer Science and Technology, Chongqing, China
  • University of Macau, Department of Computer and Information Science, Macau (former)


According to our database1, Bo Liu authored at least 17 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2023
A Versatile Detection Method for Various Contrast Enhancement Manipulations.
IEEE Trans. Circuits Syst. Video Technol., February, 2023

DLBD: A Self-Supervised Direct-Learned Binary Descriptor.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Self-Supervised Image Local Forgery Detection by JPEG Compression Trace.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Privacy-Preserving Color Image Feature Extraction by Quaternion Discrete Orthogonal Moments.
IEEE Trans. Inf. Forensics Secur., 2022

PGNet: Positioning Guidance Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Images.
Remote. Sens., 2022

Detecting Generated Images by Real Images.
Proceedings of the Computer Vision - ECCV 2022, 2022

FF-Net: An End-to-end Feature-Fusion Network for Double JPEG Detection and Localization.
Proceedings of the Asian Conference on Machine Learning, 2022

2021
Fooling deep neural detection networks with adaptive object-oriented adversarial perturbation.
Pattern Recognit., 2021

2020
Adversarial example generation with adaptive gradient search for single and ensemble deep neural network.
Inf. Sci., 2020

Exposing splicing forgery in realistic scenes using deep fusion network.
Inf. Sci., 2020

Crafting adversarial example with adaptive root mean square gradient on deep neural networks.
Neurocomputing, 2020

Locating splicing forgery by adaptive-SVD noise estimation and vicinity noise descriptor.
Neurocomputing, 2020

2018
Locating splicing forgery by fully convolutional networks and conditional random field.
Signal Process. Image Commun., 2018

Deep Fusion Network for Splicing Forgery Localization.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2017
Multi-object splicing forgery detection using noise level difference.
Proceedings of the IEEE Conference on Dependable and Secure Computing, 2017

2016
Multi-scale noise estimation for image splicing forgery detection.
J. Vis. Commun. Image Represent., 2016

2013
A SIFT and local features based integrated method for copy-move attack detection in digital image.
Proceedings of the IEEE International Conference on Information and Automation, 2013


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