no code implementations • ROCLING 2021 • Yu-Lin Chang, Yongfu Liao, Po-Ya Angela Wang, Mao-Chang Ku, Shu-Kai Hsieh
The rapid flow of information and the abundance of text data on the Internet have brought about the urgent demand for the construction of monitoring resources and techniques used for various purposes.
no code implementations • 29 May 2023 • Yu-Hsiang Tseng, Mao-Chang Ku, Wei-Ling Chen, Yu-Lin Chang, Shu-Kai Hsieh
We propose a `Vec2Gloss' model, which produces the gloss from the target word's contextualized embeddings.
2 code implementations • ICLR 2022 • Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi Lee
These methods facilitate the training procedure of conditional score models, as a mixture of scores can be separately estimated using a score model and a classifier.
1 code implementation • ICCV 2021 • Ning-Hsu Wang, Ren Wang, Yu-Lun Liu, Yu-Hao Huang, Yu-Lin Chang, Chia-Ping Chen, Kevin Jou
In this paper, we propose a method to estimate not only a depth map but an AiF image from a set of images with different focus positions (known as a focal stack).
1 code implementation • CVPR 2021 • Yi-Chen Lo, Chia-Che Chang, Hsuan-Chao Chiu, Yu-Hao Huang, Chia-Ping Chen, Yu-Lin Chang, Kevin Jou
In this paper, we present CLCC, a novel contrastive learning framework for color constancy.
no code implementations • 20 Oct 2020 • Chien-Chuan Su, Ren Wang, Hung-Jin Lin, Yu-Lun Liu, Chia-Ping Chen, Yu-Lin Chang, Soo-Chang Pei
It aims to preserve visual information of HDR images in a medium with a limited dynamic range.
1 code implementation • ECCV 2020 • Ke-Chi Chang, Ren Wang, Hung-Jin Lin, Yu-Lun Liu, Chia-Ping Chen, Yu-Lin Chang, Hwann-Tzong Chen
Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications.