Recruit

The School of Social Data Science, Hitotsubashi University is actively recruiting both the undergraduate and post-graduate students. Visit our official webpage at (https://www.sds.hit-u.ac.jp/).

If you wish to join our faculty, please feel free to contact me with the contact form. If you wish to enter the graduate school and to join my laboratory, it would be a good idea to contact me in advance. Then, let's have a brief meeting to talk about your research interest.

News

Research

Our lab studies on computer graphics and computer vision techniques, focusing on image, video, and geometry processing for 2D and 3D real-world data and their purpose-specific visualization. You can find recent work of our lab in the following list.

You can also find the entire list of projects from the [RESEARCH] page.

If you are interested in joining our lab as an under- and post-graduate student (and also postdoc), please also visit the [JOIN US] page.

X-ray 3D Fiber Orientation Tomography via Alternating Optimization of Scattering Coefficients and Directions

NDT

applications

Reference: Tomoki Mori, Yutaka Ohtake, Tatsuya Yatagawa, Kazuhiro Kido, Yasunori Tsuboi, "X-ray 3D Fiber Orientation Tomography via Alternating Optimization of Scattering Coefficients and Directions," Journal of Nondestructive Evaluation (2024).

Primitive-based Model Reduction for Huge 3D Meshes of Industrial Plants

graphics

geometry

applications

Reference: Haruki Hattori, Yutaka Ohtake, Tatsuya Yatagawa, Kazutoshi Miyamoto, Masashi Hirota, "Primitive-based Model Reduction for Huge 3D Meshes of Industrial Plants," IEEE Conference on Virtual Reality and 3D User Interfaces 2024.

Learning-Based Spotlight Position Optimization for Non-Line-of-Sight Human Localization and Posture Classification

vision

deep learning

Reference: Sreenithy Chandran, Tatsuya Yatagawa, Hiroyuki Kubo, Suren Jayasuriya, "Learning-Based Spotlight Position Optimization for Non-Line-of-Sight Human Localization and Posture Classification," .

Learning Self-Prior for Mesh Inpainting Using Self-Supervised Graph Convolutional Networks

graphics

geometry

deep learning

Reference: Shota Hattori, Tatsuya Yatagawa, Yutaka Ohtake, Hiromasa Suzuki, "Learning Self-Prior for Mesh Inpainting Using Self-Supervised Graph Convolutional Networks," IEEE Transactions on Visualization and Computer Graphics (2024).

Event-Based Camera Simulation Using Monte Carlo Path Tracing with Adaptive Denoising

graphics

rendering

Reference: Yuta Tsuji, Tatsuya Yatagawa, Hiroyuki Kubo, Shigeo Morishima, "Event-Based Camera Simulation Using Monte Carlo Path Tracing with Adaptive Denoising," IEEE International Conference on Image Processing 2023.

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