TL; DR: Reducing memory footprint for on-chip NN deployment by processing images line by line
J. Li, F. Li, and D. Iso. Learning Hierarchical Line Buffer for Image Processing. ICCV 2025. [paper][code]
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TL; DR: A dual-pixel dataset containing multiple types of information and an NN-based dual-pixel image simulator.
F. Li, H. Guo, H. Santo, F. Okura, and Y. Matsushita. Learning to Synthesize Photorealistic Dual-pixel Images from RGBD Frames. ICCP 2023. [paper][code & dataset]
TL; DR: A new formulation to model the linear regression problems with unknown correspondences. A remarkably simple yet effective optimization algorithm is also presented.
F. Li, K. Fujiwara, F. Okura, and Y. Matsushita. Shuffled Linear Regression with Outliers in Both Covariates and Responses. IJCV 2022. [paper]
F. Li, K. Fujiwara, F. Okura, and Y. Matsushita. Generalized Shuffled Linear Regression. ICCV 2021 (oral). [paper] [supp] [code]
TL; DR: There are 24 ambiguities of the PCA-based canonical poses of point clouds! Correctly identifying them leads to much better performances in deep rotation-invariant point cloud analysis.
F. Li, K. Fujiwara, F. Okura, and Y. Matsushita. A Closer Look at Rotation-invariant Deep Point Cloud Analysis. ICCV 2021. [paper] [supp] [code]
TL; DR: Geometric and probabilistic point cloud registration algorithms are developed independently so far. We propose a framework that unifies them together for an information-geometric perspective.
F. Li, K. Fujiwara, and Y. Matsushita. Toward A Unified Framework for Point Set Registration. ICRA 2021. [paper]
TL; DR: Adaptive Bayesian filter based on Bingham distribution for pose estimation in SE(3) .
F. Li, GAG. Ricardez, J. Takamatsu, and T. Ogasawara. Adaptive Bingham Distribution Based Filter for SE(3) Estimation. ICRA 2019. [paper]
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