Jun Han
Orcid: 0000-0002-7286-062XAffiliations:
- Hong Kong University of Science and Technology, Hong Kong, SAR, China
- Chinese University of Hong Kong-Shenzhen (CUHK-SZ), Shenzhen, China (former)
- University of Notre Dame, Notre Dame, IN, USA (former)
According to our database1,
Jun Han
authored at least 29 papers
between 2019 and 2025.
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Bibliography
2025
TexGS-VolVis: Expressive Scene Editing for Volume Visualization via Textured Gaussian Splatting.
CoRR, July, 2025
IEEE Trans. Vis. Comput. Graph., June, 2025
Proceedings of the Companion of the 2025 International Conference on Management of Data, 2025
ST<sup>2</sup>VR: An Interactive Authoring System for SpatioTemporal STorytelling in Virtual Reality with Hierarchical Narrative Structure.
Proceedings of the 18th IEEE Pacific Visualization Conference, 2025
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
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
STNet: An End-to-End Generative Framework for Synthesizing Spatiotemporal Super-Resolution Volumes.
IEEE Trans. Vis. Comput. Graph., 2022
IEEE Trans. Vis. Comput. Graph., 2022
Comput. Graph. Forum, 2022
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
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
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
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
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019