Lijun Zhao

Orcid: 0000-0002-2305-1914

Affiliations:

Taiyuan University of Science and Technology, Institute of Digital Media and Communication, China
Beijing Jiaotong University, Institute of Information Science, China

According to our database¹, Lijun Zhao authored at least 34 papers between 2015 and 2023.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2023

Joint depth map super-resolution method via deep hybrid-cross guidance filter.

[BibT_eX]

[DOI]

Pattern Recognit., April, 2023

Learning deep texture-structure decomposition for low-light image restoration and enhancement.

[BibT_eX]

[DOI]

Neurocomputing, March, 2023

Boundary-constrained interpretable image reconstruction network for deep compressive sensing.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2023

Deep Arbitrary-Scale Unfolding Network for Color-Guided Depth Map Super-Resolution.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition and Computer Vision - 6th Chinese Conference, 2023

WDU-Net: Wavelet-Guided Deep Unfolding Network for Image Compressed Sensing Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition and Computer Vision - 6th Chinese Conference, 2023

Explainable Unfolding Network For Joint Edge-Preserving Depth Map Super-Resolution.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

A Joint Model-Driven Unfolding Network for Degraded Low-Quality Color-Depth Images Enhancement.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Image Processing, 2023

Edge-Guided Interpretable Neural Network for Image Compressive Sensing Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the Image and Graphics - 12th International Conference, 2023

2022

LMDC: Learning a multiple description codec for deep learning-based image compression.

[BibT_eX]

[DOI]

Multim. Tools Appl., 2022

Deep MRI glioma segmentation via multiple guidances and hybrid enhanced-gradient cross-entropy loss.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2022

SF-SegFormer: Stepped-Fusion Segmentation Transformer for Brain Tissue Image via Inter-Group Correlation and Enhanced Multi-layer Perceptron.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Understanding and Analysis - 26th Annual Conference, 2022

D<sup>2</sup>-UTransforIner: Deep Modulated Dual-UTransformer for Multiple Description Image Enhancement.

[BibT_eX]

[DOI]

Proceedings of the 5th IEEE International Conference on Multimedia Information Processing and Retrieval, 2022

2021

MRANet: Multi-atrous residual attention Network for stereo image super-resolution.

[BibT_eX]

[DOI]

J. Vis. Commun. Image Represent., 2021

Brain tumor segmentation of multi-modality MR images via triple intersecting U-Nets.

[BibT_eX]

[DOI]

Neurocomputing, 2021

2020

Deep Optimized Multiple Description Image Coding via Scalar Quantization Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Concurrently Extrapolating and Interpolating Networks for Continuous Model Generation.

[BibT_eX]

[DOI]

CoRR, 2020

HDA Video Transmission Scheme for DASH.

[BibT_eX]

[DOI]

IEEE Access, 2020

2019

Multiple Description Convolutional Neural Networks for Image Compression.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. Video Technol., 2019

Local activity-driven structural-preserving filtering for noise removal and image smoothing.

[BibT_eX]

[DOI]

Signal Process., 2019

Simultaneous color-depth super-resolution with conditional generative adversarial networks.

[BibT_eX]

[DOI]

Pattern Recognit., 2019

Iterative range-domain weighted filter for structural preserving image smoothing and de-noising.

[BibT_eX]

[DOI]

Multim. Tools Appl., 2019

Learning a virtual codec based on deep convolutional neural network to compress image.

[BibT_eX]

[DOI]

J. Vis. Commun. Image Represent., 2019

Deep Multiple Description Coding by Learning Scalar Quantization.

[BibT_eX]

[DOI]

Proceedings of the Data Compression Conference, 2019

2018

Cascaded reconstruction network for compressive image sensing.

[BibT_eX]

[DOI]

EURASIP J. Image Video Process., 2018

Virtual Codec Supervised Re-Sampling Network for Image Compression.

[BibT_eX]

[DOI]

CoRR, 2018

Mixed-Resolution Image Representation and Compression with Convolutional Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Dual-Streams Edge Driven Encoder-Decoder Network for Image Super-Resolution.

[BibT_eX]

[DOI]

IEEE Access, 2018

2017

Two-stage filtering of compressed depth images with Markov Random Field.

[BibT_eX]

[DOI]

Signal Process. Image Commun., 2017

Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network.

[BibT_eX]

[DOI]

CoRR, 2017

Local Activity-tuned Image Filtering for Noise Removal and Image Smoothing.

[BibT_eX]

[DOI]

CoRR, 2017

Single depth image super-resolution with multiple residual dictionary learning and refinement.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Multimedia and Expo, 2017

Convolutional neural network-based depth image artifact removal.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016

Joint iterative guidance filtering for compressed depth images.

[BibT_eX]

[DOI]

Proceedings of the 2016 Visual Communications and Image Processing, 2016

2015

Scalable Coding of Depth Images with Synthesis-Guided Edge Detection.

[BibT_eX]

[DOI]

KSII Trans. Internet Inf. Syst., 2015

Lijun Zhao

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