tatsy.lab

Hitotsubashi University
School of Social Data Science
Graphics and Vision Labratory

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Welcome

Our lab studies 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.
Learn more about our research directions at [RESEARCH]. Specific published work is available at [PROJECTS].

Recruit

We welcome prospective graduate students, including international students, who are interested in joining our lab. If you are interested in our research topics, please get in touch through the contact form below.
Contact us through this form: [[CONTACT FORM]]

News

member

Our lab welcomes 1 undergraduate student.

paper

Joint research of Dr. Yatagawa with the National Institute of Advanced Industrial Science and Technology (AIST) has been presented at SPIE Advanced Lithography + Patterning 2026 at San Jose, USA.

Paper
paper

Joint research by Dr. Yatagawa with the University of Tokyo and Zodiac Co., Ltd. was presented at the 15th International Conference on Industrial Computed Tomography (iCT), held at the University of Applied Sciences Upper Austria in Austria.

Reference
paper

Joint research by Dr. Yatagawa with the University of Tokyo were presented at the 15th International Conference on Industrial Computed Tomography (iCT), held at the University of Applied Sciences Upper Austria in Austria.

Reference
paper

Joint research by Dr. Yatagawa and the University of Tokyo has been published in the international journal Computational Visual Media.

Reference
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Recent Projects

NeMCoF: Neural Material Composition Fields for Material Decomposition in Sparse-View Spectral X-ray CT

NDT
applications
NeMCoF: Neural Material Composition Fields for Material Decomposition in Sparse-View Spectral X-ray CT
Reference: Takumi Hotta, Tatsuya Yatagawa, Yutaka Ohtake, Toru Aoki, “NeMCoF: Neural Material Composition Fields for Material Decomposition in Sparse-View Spectral X-ray CT,” Journal of Nondestructive Evaluation (2025).

Towards accelerating polarization path tracing of multi-bounce Smith microfacet BSDFs

graphics
rendering
Towards accelerating polarization path tracing of multi-bounce Smith microfacet BSDFs
Reference: Hidehito Ohba, Tatsuya Yatagawa, Shigeo Morishima, “Towards accelerating polarization path tracing of multi-bounce Smith microfacet BSDFs,” (2025).

Learning Scatter Artifact Correction in Cone-Beam X-Ray CT Using Incomplete Projections with Beam Hole Array

NDT
applications
Learning Scatter Artifact Correction in Cone-Beam X-Ray CT Using Incomplete Projections with Beam Hole Array
Reference: Haruki Hattori, Tatsuya Yatagawa, Yutaka Ohtake, Hiromasa Suzuki, “Learning Scatter Artifact Correction in Cone-Beam X-Ray CT Using Incomplete Projections with Beam Hole Array,” Journal of Nondestructive Evaluation (2024).

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

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

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

graphics
geometry
deep learning
Learning Self-Prior for Mesh Inpainting Using Self-Supervised Graph Convolutional Networks
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).
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Access

186-8601
2-1, Naka, Kunitachi, Tokyo
Room 229, East Main Bldg.
Hitotsubashi University School of Social Data Science
Graphics and Vision Labratory