3 papers
cs.CV2026
FDIF: Formula-Driven supervised Learning with Implicit Functions for 3D Medical Image Segmentation
Yukinori Yamamoto, Kazuya Nishimura, Tsukasa Fukusato +3
Deep learning-based 3D medical image segmentation methods relies on large-scale labeled datasets, yet acquiring such data is difficult due to privacy constraints and the high cost…
cs.GR2025
Physics-Aware Fluid Field Generation from User Sketches Using Helmholtz-Hodge Decomposition
Ryuichi Miyauchi, Hengyuan Chang, Tsukasa Fukusato +2
Fluid simulation techniques are widely used in various fields such as film production, but controlling complex fluid behaviors remains challenging. While recent generative models e…
cs.GR2025
Computational Design and Fabrication of Protective Foam
Tsukasa Fukusato, Naoki Kita
This paper proposes a method to design protective foam for packaging 3D objects. Users first load a 3D object and define a block-based design space by setting the block resolution…