Hao-Yu Fang — accepted AI-conference papers

2021

ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel Loss

Wei-Ting Chen, Hao-Yu Fang, Cheng-Lin Hsieh, Cheng-Che Tsai, I-Hsiang Chen, Jian-Jiun Ding +1

ICCV 2021poster

Snow is a highly complicated atmospheric phenomenon that usually contains snowflake, snow streak, and veiling effect (similar to the haze or the mist). In this literature, we propose a single image desnowing algorithm to address the diversity of snow particles in shape and size. First, to better rep…

Cited by 232 PDF ↗code ↗Scholar ↗

2021

All Characteristics Preservation: Single Image Dehazing based on Hierarchical Detail Reconstruction Wavelet Decomposition Network

Wei-Ting Chen, Hao-Yu Fang, Cheng-Che Tsai, Jian-Jiun Ding, Sy-Yen Kuo

IROS 2021poster

Single image haze removal is crucial in computer vision. In open literatures, two kinds of dehazing strategies (prior-based and learning-based methods) have been developed. However, they have a trade-off between detail preservation and the image quality. Prior-based methods reconstruct the detail we…

Cited by 1 Source ↗Scholar ↗

2020

JSTASR: Joint Size and Transparency-Aware Snow Removal Algorithm Based on Modified Partial Convolution and Veiling Effect Removal

Wei-Ting Chen, Hao-Yu Fang, Jian-Jiun Ding, Cheng-Che Tsai, Sy-Yen Kuo

ECCV 2020poster

Snow removal usually affects the performance of computer vision. Comparing with other atmospheric phenomenon (e.g., haze and rain), snow is more complicated due to its transparency, various size, and accumulation of veiling effect, which make single image de-snowing more challenging. In this paper,…

Cited by 211 Source ↗PDF ↗code ↗Scholar ↗