Search Results for author: Yu-Lin Chang

Found 7 papers, 4 papers with code

Keyword-centered Collocating Topic Analysis

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.

Word Embeddings

Vec2Gloss: definition modeling leveraging contextualized vectors with Wordnet gloss

no code implementations29 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.

Denoising Likelihood Score Matching for Conditional Score-based Data Generation

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.

Image Generation

Bridging Unsupervised and Supervised Depth from Focus via All-in-Focus Supervision

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).

Depth Estimation

Explorable Tone Mapping Operators

no code implementations20 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.

Tone Mapping

Learning Camera-Aware Noise Models

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.

Noise Estimation

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