9 code implementations • ICCV 2017 • Yi-Hsin Chen, Wei-Yu Chen, Yu-Ting Chen, Bo-Cheng Tsai, Yu-Chiang Frank Wang, Min Sun
Despite the recent success of deep-learning based semantic segmentation, deploying a pre-trained road scene segmenter to a city whose images are not presented in the training set would not achieve satisfactory performance due to dataset biases.
13 code implementations • ICLR 2019 • Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira, Yu-Chiang Frank Wang, Jia-Bin Huang
Few-shot classification aims to learn a classifier to recognize unseen classes during training with limited labeled examples.
no code implementations • 22 Mar 2020 • Wei-Yu Chen, Hisao Ishibuchi, Ke Shang
In other studies, it is shown that the objective space discretization improves the performance on combinatorial multi-objective problems.
no code implementations • 4 Jul 2020 • Wei-Yu Chen, Hisao Ishibuhci, Ke Shang
Subset selection is a popular topic in recent years and a number of subset selection methods have been proposed.
no code implementations • 31 Jan 2023 • Chung-I Huang, Wei-Yu Chen, Wei Jan Ko, Jih-Sheng Chang, Chen-Kai Sun, Hui Hung Yu, Fang-Pang Lin
This study presents an open data-market platform and a dataset containing 160, 000 markers and 18, 000 images.
no code implementations • CVPR 2023 • Jen-Hao Rick Chang, Wei-Yu Chen, Anurag Ranjan, Kwang Moo Yi, Oncel Tuzel
Specifically, we train a set transformer that, given a small number of local neighbor points along a light ray, provides the intersection point, the surface normal, and the material blending weights, which are used to render the outcome of this light ray.
no code implementations • ROCLING 2022 • Ting-Wei Chen, Wei-Ting Lin, Chia-Ping Chen, Chung-Li Lu, Bo-Cheng Chan, Yu-Han Cheng, Hsiang-Feng Chuang, Wei-Yu Chen
In this paper, we use several combinations of feature front-end modules and attention mechanisms to improve the performance of our speaker verification system.
no code implementations • ROCLING 2022 • Chia-Chuan Liu, Sung-Jen Huang, Chia-Ping Chen, Chung-Li Lu, Bo-Cheng Chan, Yu-Han Cheng, Hsiang-Feng Chuang, Wei-Yu Chen
The proposed system achieves PSDS (Polyphonic sound event detection score)-scenario 1, 2 of 40. 8% and 67. 7% outperforms the baseline system of 34. 4% and 57. 2% on the DCASE 2022 Task4 validation dataset.