| dc.contributor | 資科系 | |
| dc.creator (作者) | 彭彥璁 | |
| dc.creator (作者) | Peng, Yan-Tsung | |
| dc.creator (作者) | Cheng, Kai-Han;Fang, I-Sheng;Peng, Wen-Yi;Wu, Jr-Shian | |
| dc.date (日期) | 2022-02 | |
| dc.date.accessioned | 6-Feb-2023 14:30:33 (UTC+8) | - |
| dc.date.available | 6-Feb-2023 14:30:33 (UTC+8) | - |
| dc.date.issued (上傳時間) | 6-Feb-2023 14:30:33 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/143301 | - |
| dc.description.abstract (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. | |
| dc.format.extent | 104 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | IEEE Signal Processing Letters, Vol.29, pp.568-572 | |
| dc.subject (關鍵詞) | Image reflection removal; knowledge distillation; content disentanglement | |
| dc.title (題名) | Single Image Reflection Removal Based on Knowledge-Distilling Content Disentanglement | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.1109/LSP.2022.3148668 | |
| dc.doi.uri (DOI) | https://doi.org/10.1109/LSP.2022.3148668 | |
