- > 연구실 소개 > 연구분야
- Reinforcement Learning for Commerical Sports Game
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Reinforcement Learning for Commerical Sports Game researches with JoyCity Corporation (Online Game Company)
- Neural Rendering-Based 3D Scene Style Transfer
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Neural Rendering-Based 3D Scene Style Transfer Method via Semantic Understanding Using a Single Style Image
- 3D Semantic Estimation from Monocular Videos
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Depth Prior-Guided 3D Voxel Feature Fusion for 3D Semantic Estimation from Monocular Videos
- Realistic Marine Image Generation Using a Multimodal Style Transfer Network
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Realistic Marine Image Generation Using a Multimodal Style Transfer Network for Training Autonomous Vessels
- Virtual Learning Simulator for Autonomous Vehicles
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Virtual Scenario Simulation and Modeling Framework in Autonomous Driving Simulators
- 3D Scene Reconstruction from Single 2D Images
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3D Scene Reconstruction from Single 2D Images of Indoor Scenes
- Metaverse 3D Space Creation and Automatic Scenario Creation
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Large Language Model Driven Scenario Generation
- Reproduction of Accident Video-based Virtual Reality 3D Environment
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Reproduction of Accident Video-based Virtual Reality 3D Environment by 3D data estimation from 2D videos
- Game and Robot Intelligence / Machine Learning Research
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- Virtual Learning Simulator for Robots
- Automatic generation of 3D virtual environment
- Autonomous mobile Robot Intelligence
- Game, robot intelligence, NUI / NUX engine development
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- Real-time 3D terrain rendering engine
- Interactive learning robot engine
- Interactive sensibility intelligent character engine
- NUI / NUX engine
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