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    题名: Single Image Reflection Removal Based on Knowledge-Distilling Content Disentanglement
    作者: 彭彥璁
    Peng, Yan-Tsung
    Cheng, Kai-Han;Fang, I-Sheng;Peng, Wen-Yi;Wu, Jr-Shian
    贡献者: 資科系
    关键词: Image reflection removal;knowledge distillation;content disentanglement
    日期: 2022-02
    上传时间: 2023-02-06 14:30:33 (UTC+8)
    摘要: When we shoot pictures through transparent media, such as glass, reflection can undesirably occur, obscuring the scene we intended to capture. Therefore, removing reflection is practical in image restoration. However, a reflective scene mixed with that behind the glass is challenging to be separated, considered significantly ill-posed. This letter addresses the single image reflection removal (SIRR) problem by proposing a knowledge-distilling-based content disentangling model that can effectively decompose the transmission and reflection layers. The experiments on benchmark SIRR datasets demonstrate that our method performs favorably against state-of-the-art SIRR methods.
    關聯: IEEE Signal Processing Letters, Vol.29, pp.568-572
    数据类型: article
    DOI 連結: https://doi.org/10.1109/LSP.2022.3148668
    DOI: 10.1109/LSP.2022.3148668
    显示于类别:[資訊科學系] 期刊論文

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