1 code implementation • 27 Apr 2024 • Zelong Zeng, Kaname Tomite
In anomaly segmentation for complex driving scenes, state-of-the-art approaches utilize anomaly scoring functions to calculate anomaly scores.
1 code implementation • 14 Nov 2022 • Zelong Zeng, Fan Yang, Hong Liu, Shin'ichi Satoh
However, this type of method normally ignores the crucial knowledge hidden in the data (e. g., intra-class information variation), which is harmful to the generalization of the trained model.
1 code implementation • 17 Jun 2022 • Zelong Zeng, Fan Yang, Zheng Wang, Shin'ichi Satoh
Most deep metric learning (DML) methods employ a strategy that forces all positive samples to be close in the embedding space while keeping them away from negative ones.
1 code implementation • 22 May 2022 • Zelong Zeng, Zheng Wang, Fan Yang, Shin'ichi Satoh
The large variation of viewpoint and irrelevant content around the target always hinder accurate image retrieval and its subsequent tasks.
no code implementations • 11 May 2019 • Zelong Zeng, Zhixiang Wang, Zheng Wang, Yinqiang Zheng, Yung-Yu Chuang, Shin'ichi Satoh
To demonstrate the illumination issue and to evaluate our model, we construct two large-scale simulated datasets with a wide range of illumination variations.