Yi Liu

Orcid: 0000-0002-5177-5522

Affiliations:
  • Xidian University, MOE Key Laboratory of Electronic Equipment Structure Design, Xi'an, China
  • Xidian University, School of Mechano-Electronic Engineering, Center for Complex Systems, Xi'an, China


According to our database1, Yi Liu authored at least 14 papers between 2017 and 2024.

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

Timeline

Legend:

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Bibliography

2024
Deep unsupervised part-whole relational visual saliency.
Neurocomputing, January, 2024

2022
Disentangled Capsule Routing for Fast Part-Object Relational Saliency.
IEEE Trans. Image Process., 2022

Engaging Part-Whole Hierarchies and Contrast Cues for Salient Object Detection.
IEEE Trans. Circuits Syst. Video Technol., 2022

Bi-Directional Progressive Guidance Network for RGB-D Salient Object Detection.
IEEE Trans. Circuits Syst. Video Technol., 2022

Part-Object Relational Visual Saliency.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

2021
Joint Cross-Modal and Unimodal Features for RGB-D Salient Object Detection.
IEEE Trans. Multim., 2021

Integrating Part-Object Relationship and Contrast for Camouflaged Object Detection.
IEEE Trans. Inf. Forensics Secur., 2021

2020
Deep Salient Object Detection With Contextual Information Guidance.
IEEE Trans. Image Process., 2020

2019
Salient Object Detection via Two-Stage Graphs.
IEEE Trans. Circuits Syst. Video Technol., 2019

Salient object detection employing a local tree-structured low-rank representation and foreground consistency.
Pattern Recognit., 2019

Employing Deep Part-Object Relationships for Salient Object Detection.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: A review.
Inf. Fusion, 2018

2017
Salient object detection based on super-pixel clustering and unified low-rank representation.
Comput. Vis. Image Underst., 2017

Sparse Representation based Multi-sensor Image Fusion: A Review.
CoRR, 2017


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