1 code implementation • CVPR 2023 • Shogo Sato, Yasuhiro Yao, Taiga Yoshida, Takuhiro Kaneko, Shingo Ando, Jun Shimamura
Intrinsic image decomposition (IID) is the task that decomposes a natural image into albedo and shade.
no code implementations • 4 Oct 2022 • Yasuhiro Yao, Ryoichi Ishikawa, Shingo Ando, Kana Kurata, Naoki Ito, Jun Shimamura, Takeshi Oishi
Moreover, under various LiDAR-camera calibration errors, the proposed method reduced the depth estimation MAE to 0. 34-0. 93 times from previous depth completion methods.
no code implementations • 25 Jun 2020 • Yasuhiro Yao, Menandro Roxas, Ryoichi Ishikawa, Shingo Ando, Jun Shimamura, Takeshi Oishi
Our experiments show that our method can outperform previous unsupervised and semi-supervised depth completion methods in terms of accuracy.
no code implementations • 16 Mar 2019 • Yongqing Sun, Pranav Shenoy K P, Jun Shimamura, Atsushi Sagata
Low level features like edges and textures play an important role in accurately localizing instances in neural networks.
no code implementations • 12 Dec 2018 • Shisha Liao, Yongqing Sun, Chenqiang Gao, Pranav Shenoy K P, Song Mu, Jun Shimamura, Atsushi Sagata
Weakly-supervised instance segmentation, which could greatly save labor and time cost of pixel mask annotation, has attracted increasing attention in recent years.