Jun Han

Orcid: 0000-0002-7286-062X

Affiliations:
  • Chinese University of Hong Kong-Shenzhen (CUHK-SZ), Shenzhen, China
  • University of Notre Dame, Notre Dame, IN, USA (former)


According to our database1, Jun Han authored at least 25 papers between 2019 and 2024.

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

Timeline

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Bibliography

2024
KD-INR: Time-Varying Volumetric Data Compression via Knowledge Distillation-Based Implicit Neural Representation.
IEEE Trans. Vis. Comput. Graph., October, 2024

2023
CoordNet: Data Generation and Visualization Generation for Time-Varying Volumes via a Coordinate-Based Neural Network.
IEEE Trans. Vis. Comput. Graph., December, 2023

DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization.
IEEE Trans. Vis. Comput. Graph., August, 2023

GMT: A deep learning approach to generalized multivariate translation for scientific data analysis and visualization.
Comput. Graph., May, 2023

2022
VCNet: A generative model for volume completion.
Vis. Informatics, 2022

STNet: An End-to-End Generative Framework for Synthesizing Spatiotemporal Super-Resolution Volumes.
IEEE Trans. Vis. Comput. Graph., 2022

SSR-TVD: Spatial Super-Resolution for Time-Varying Data Analysis and Visualization.
IEEE Trans. Vis. Comput. Graph., 2022

SurfNet: Learning Surface Representations via Graph Convolutional Network.
Comput. Graph. Forum, 2022

TSR-VFD: Generating temporal super-resolution for unsteady vector field data.
Comput. Graph., 2022

AQX: Explaining Air Quality Forecast for Verifying Domain Knowledge using Feature Importance Visualization.
Proceedings of the IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22, 2022

Scalar2Vec: Translating Scalar Fields to Vector Fields via Deep Learning.
Proceedings of the 15th IEEE Pacific Visualization Symposium, 2022

2021
V2V: A Deep Learning Approach to Variable-to-Variable Selection and Translation for Multivariate Time-Varying Data.
IEEE Trans. Vis. Comput. Graph., 2021

Reconstructing Unsteady Flow Data From Representative Streamlines via Diffusion and Deep-Learning-Based Denoising.
IEEE Computer Graphics and Applications, 2021

Hierarchical Self-supervised Learning for Medical Image Segmentation Based on Multi-domain Data Aggregation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020
TSR-TVD: Temporal Super-Resolution for Time-Varying Data Analysis and Visualization.
IEEE Trans. Vis. Comput. Graph., 2020

FlowNet: A Deep Learning Framework for Clustering and Selection of Streamlines and Stream Surfaces.
IEEE Trans. Vis. Comput. Graph., 2020

TransRes: A Deep Transfer Learning Approach to Migratable Image Super-Resolution in Remote Urban Sensing.
Proceedings of the 17th Annual IEEE International Conference on Sensing, 2020

PQA-CNN: Towards Perceptual Quality Assured Single-Image Super-Resolution in Remote Sensing.
Proceedings of the 28th IEEE/ACM International Symposium on Quality of Service, 2020

SSR-VFD: Spatial Super-Resolution for Vector Field Data Analysis and Visualization.
Proceedings of the 2020 IEEE Pacific Visualization Symposium, 2020

2019
Flow Field Reduction Via Reconstructing Vector Data From 3-D Streamlines Using Deep Learning.
IEEE Computer Graphics and Applications, 2019

A Deep Learning Approach to Selecting Representative Time Steps for Time-Varying Multivariate Data.
Proceedings of the 30th IEEE Visualization Conference, 2019

HFA-Net: 3D Cardiovascular Image Segmentation with Asymmetrical Pooling and Content-Aware Fusion.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

ContourNet: Salient Local Contour Identification for Blob Detection in Plasma Fusion Simulation Data.
Proceedings of the Advances in Visual Computing, 2019

TransLand: An Adversarial Transfer Learning Approach for Migratable Urban Land Usage Classification using Remote Sensing.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Biomedical Image Segmentation via Representative Annotation.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019


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