Depth assisted novel view synthesis using few images
文献类型：期刊论文
| 作者 | Li, Qian1; Fu, Rao1; Tang, Fulin2
|
| 刊名 | IMAGE AND VISION COMPUTING
 |
| 出版日期 | 2024-07-01 |
| 卷号 | 147页码:9 |
| 关键词 | Neural radiance fields View synthesis Image warping |
| ISSN号 | 0262-8856 |
| DOI | 10.1016/j.imavis.2024.105079 |
| 通讯作者 | Fu, Rao(rao.fu@inria.fr) |
| 英文摘要 | In this paper, we introduce a novel approach to improve the performance of Neural Radiance Fields (NeRF) from limited input views. NeRF has exhibited impressive capabilities in producing photo-realistic renderings when trained on dense input views, but its performance degrades as the number of training views decreases. Our key insight is that the original NeRF lacks geometric regularization and appearance information due to limited inputs, resulting in an over-fitting issue. To address this challenge, we present a novel method: first, a global sampling method with geometric regularization is employed by utilizing warped images as additional pseudoviews, which optimizes the multi-view consistency during the training. Second, we introduce a local patch sampling technique with perceptual regularization to ensure pixel correspondence in appearance. Furthermore, we incorporate depth information for explicit geometry regularization. We evaluate our method on the DTU dataset and LLFF dataset from a different number of inputs. Extensive evaluations demonstrate that our approach outperforms existing benchmarks across various metrics, achieving state-of-the-art results. |
| WOS研究方向 | Computer Science ; Engineering ; Optics |
| 语种 | 英语 |
| WOS记录号 | WOS:001244560700001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.ia.ac.cn/handle/173211/58701]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_机器人视觉团队 |
| 通讯作者 | Fu, Rao |
| 作者单位 | 1.Inria, Le Chesnay Rocquencourt, France 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Qian,Fu, Rao,Tang, Fulin. Depth assisted novel view synthesis using few images[J]. IMAGE AND VISION COMPUTING,2024,147:9. |
| APA | Li, Qian,Fu, Rao,&Tang, Fulin.(2024).Depth assisted novel view synthesis using few images.IMAGE AND VISION COMPUTING,147,9. |
| MLA | Li, Qian,et al."Depth assisted novel view synthesis using few images".IMAGE AND VISION COMPUTING 147(2024):9. |
入库方式： OAI收割
来源：自动化研究所
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