| アイテムタイプ |
itemtype_ver1(1) |
| 公開日 |
2026-02-05 |
| タイトル |
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|
タイトル |
Combining Pre-trained and Self-supervised Reconstruction for Coded Light-Field Imaging |
|
言語 |
en |
| 著者 |
Inoue, Tomoki
Tsutake, Chihiro
Takahashi, Keita
Fujii, Toshiaki
|
| アクセス権 |
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|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 権利 |
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|
権利情報 |
© 2026 The Institute of Image Information and Television Engineers |
|
言語 |
en |
| 内容記述 |
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|
内容記述タイプ |
Abstract |
|
内容記述 |
We propose a hybrid reconstruction method for coded light-field imaging. Most previous methods utilized pre-trained reconstruction, in which the reconstruction process was first pre-trained on a light-field dataset taken from various 3-D scenes and then applied to new target 3-D scenes. However, pre-trained reconstruction is not necessarily optimal for a specific 3-D scene and sometimes results in insufficient reconstruction quality for the fine details. To address this issue, we first introduce a method of self-supervised reconstruction that focuses on the data observed from a specific 3-D scene. To this end, we incorporate a learning-based 3-D representation technique called neural radiance fields (NeRFs) into the framework of coded light-field imaging. Moreover, we combine pre-trained and self-supervised approaches seamlessly to synergize the strengths of both. Experimental results demonstrate that our method can achieve better reconstruction quality consistently over various 3-D scenes than the previous pre-trained methods. |
|
言語 |
en |
| 出版者 |
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|
出版者 |
映像メディア情報学会 |
|
言語 |
ja |
| 出版者 |
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出版者 |
The Institute of Image Information and Television Engineers |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプresource |
http://purl.org/coar/resource_type/c_6501 |
|
タイプ |
journal article |
| 出版タイプ |
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|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| ID登録 |
|
|
ID登録 |
10.18999/2013911 |
|
ID登録タイプ |
JaLC |
| 関連情報 |
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|
関連タイプ |
isVersionOf |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
https://doi.org/10.3169/mta.14.2 |
| 収録物識別子 |
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|
収録物識別子タイプ |
EISSN |
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収録物識別子 |
2186-7364 |
| 書誌情報 |
en : ITE Transactions on Media Technology and Applications
巻 14,
号 1,
p. 2-10,
発行日 2026-01-01
|
14_2-1.pdf (3.2 MB)
MTA2026-inoue-ResearchData.zip (3.3 MB)
