Search Results for author: Hao-Hsiang Yang

Found 9 papers, 7 papers with code

RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning

1 code implementation18 Sep 2022 Wei-Ting Chen, I-Hsiang Chen, Chih-Yuan Yeh, Hao-Hsiang Yang, Hua-En Chang, Jian-Jiun Ding, Sy-Yen Kuo

Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision.

Learning Multiple Adverse Weather Removal via Two-Stage Knowledge Learning and Multi-Contrastive Regularization: Toward a Unified Model

1 code implementation CVPR 2022 Wei-Ting Chen, Zhi-Kai Huang, Cheng-Che Tsai, Hao-Hsiang Yang, Jian-Jiun Ding, Sy-Yen Kuo

At the KC, the student network aims to learn the comprehensive bad weather removal problem from multiple well-trained teacher networks where each of them is specialized in a specific bad weather removal problem.

Transfer Learning

Multi-modal Bifurcated Network for Depth Guided Image Relighting

2 code implementations3 May 2021 Hao-Hsiang Yang, Wei-Ting Chen, Hao-Lun Luo, Sy-Yen Kuo

This model extracts the image and the depth features by the bifurcated network in the encoder.

Decoder Image Relighting +1

S3Net: A Single Stream Structure for Depth Guided Image Relighting

1 code implementation3 May 2021 Hao-Hsiang Yang, Wei-Ting Chen, and Sy-Yen Kuo

Depth guided any-to-any image relighting aims to generate a relit image from the original image and corresponding depth maps to match the illumination setting of the given guided image and its depth map.

Decoder Image Relighting +1

Wavelet Channel Attention Module with a Fusion Network for Single Image Deraining

no code implementations17 Jul 2020 Hao-Hsiang Yang, Chao-Han Huck Yang, Yu-Chiang Frank Wang

Wavelet transform and the inverse wavelet transform are substituted for down-sampling and up-sampling so feature maps from the wavelet transform and convolutions contain different frequencies and scales.

Single Image Deraining

Y-net: Multi-scale feature aggregation network with wavelet structure similarity loss function for single image dehazing

1 code implementation31 Mar 2020 Hao-Hsiang Yang, Chao-Han Huck Yang, Yi-Chang James Tsai

Extensive experimental results demonstrate that the proposed Y-net with the W-SSIM loss function restores high-quality clear images and outperforms state-of-the-art algorithms.

Image Dehazing Single Image Dehazing +2

Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model

1 code implementation16 Aug 2018 C. -H. Huck Yang, Fangyu Liu, Jia-Hong Huang, Meng Tian, Hiromasa Morikawa, I-Hung Lin, Yi-Chieh Liu, Hao-Hsiang Yang, Jesper Tegner

Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists.

General Classification

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