We stand with Ukraine

We stand with Ukraine

Hyungki Kim

Orcid: 0000-0001-9013-2338

According to our database¹, Hyungki Kim authored at least 24 papers between 2013 and 2026.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

On csauthors.net:

Bibliography

2026

BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning.

[DOI]

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CoRR, February, 2026

Comp-PointLLM: An explainable multimodal large language model for 3D object comparison.

[DOI]

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J. Comput. Des. Eng., 2026

2025

Investigating the effects of density and opacity of rest frames for VR sickness reduction.

[DOI]

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Virtual Real., March, 2025

Optimizing image format piping and instrumentation diagram recognition: Integrating symbol and text recognition with a single backbone architecture.

[DOI]

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J. Comput. Des. Eng., 2025

Denoise yourself: Self-supervised point cloud upsampling with pretrained denoising.

[DOI]

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Expert Syst. Appl., 2025

CADuBoost: Enhancing Education in Mechanical 3D CAD Modeling Through Automated Grading and Feedback System.

[DOI]

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Comput. Appl. Eng. Educ., 2025

2024

Viewpoint-sharing method with reduced motion sickness in object-based VR/AR collaborative virtual environment.

[DOI]

Tuvshintulga Tserenchimed

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Virtual Real., September, 2024

Multimodal contrastive learning using point clouds and their rendered images.

[DOI]

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Multim. Tools Appl., September, 2024

2022

End-to-end digitization of image format piping and instrumentation diagrams at an industrially applicable level.

[DOI]

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J. Comput. Des. Eng., 2022

2021

A method of generating depth images for view-based shape retrieval of 3D CAD models from partial point clouds.

[DOI]

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Multim. Tools Appl., 2021

Dataset and method for deep learning-based reconstruction of 3D CAD models containing machining features for mechanical parts.

[DOI]

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J. Comput. Des. Eng., 2021

Deep-learning-based recognition of symbols and texts at an industrially applicable level from images of high-density piping and instrumentation diagrams.

[DOI]

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Expert Syst. Appl., 2021

2020

Method for the generation of depth images for view-based shape retrieval of 3D CAD model from partial point cloud.

[DOI]

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CoRR, 2020

Deep-learning-based retrieval of piping component catalogs for plant 3D CAD model reconstruction.

[DOI]

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Inhwan Dennis Lee

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Comput. Ind., 2020

2019

Deep-learning-based classification and retrieval of components of a process plant from segmented point clouds.

[DOI]

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CoRR, 2019

2018

Interactive 3D building modeling method using panoramic image sequences and digital map.

[DOI]

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Multim. Tools Appl., 2018

2017

Geo-registration of wide-baseline panoramic image sequences using a digital map reference.

[DOI]

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Multim. Tools Appl., 2017

Erratum to: Shape distribution-based retrieval of 3D CAD models at different levels of detail.

[DOI]

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Multim. Tools Appl., 2017

Shape distribution-based retrieval of 3D CAD models at different levels of detail.

[DOI]

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Multim. Tools Appl., 2017

Cluster rendering on large high-resolution multi-displays using X3DOM and HTML.

[DOI]

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Multim. Syst., 2017

2015

Editing 3D models on smart devices.

[DOI]

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Hiromasa Suzuki

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Comput. Aided Des., 2015

2014

A framework for the automatic 3D city modeling using the panoramic image from mobile mapping system and digital maps.

[DOI]

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Proceedings of the 2014 IEEE Virtual Reality, 2014

Collaborative Visualization of a Warfare Simulation Using a Commercial Game Engine.

[DOI]

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Proceedings of the Virtual, Augmented and Mixed Reality. Applications of Virtual and Augmented Reality, 2014

2013

Street-side city modeling from ground-level imagery and a digital map.

[DOI]

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Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference, 2013

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