Towards Domain-agnostic Depth Completion | |
Guangkai Xu1; Wei Yin4; Jianming Zhang3; Oliver Wang3; Simon Niklaus3; Simon Chen3; Jia-Wang Bian2 | |
刊名 | Machine Intelligence Research
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2024 | |
卷号 | 21期号:4页码:652-669 |
关键词 | Monocular depth estimation depth completion zero-shot generalization scene reconstruction neural network |
ISSN号 | 2731-538X |
DOI | 10.1007/s11633-024-1494-4 |
英文摘要 | Existing depth completion methods are often targeted at a specific sparse depth type and generalize poorly across task do mains. We present a method to complete sparse/semi-dense, noisy, and potentially low-resolution depth maps obtained by various range sensors, including those in modern mobile phones, or by multi-view reconstruction algorithms. Our method leverages a data-driven prior in the form of a single image depth prediction network trained on large-scale datasets, the output of which is used as an input to our model. We propose an effective training scheme where we simulate various sparsity patterns in typical task domains. In addition, we design two new benchmarks to evaluate the generalizability and robustness of depth completion methods. Our simple method shows superior cross-domain generalization ability against state-of-the-art depth completion methods, introducing a practical solution to high quality depth capture on a mobile device. |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/58565] ![]() |
专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
作者单位 | 1.Zhejiang University, Hangzhou 310058, China 2.University of Oxford, Oxford OX1 2JD, UK 3.Adobe Research, California 95110, USA 4.DaJiang Technology, Shenzhen 518057, China |
推荐引用方式 GB/T 7714 | Guangkai Xu, Wei Yin, Jianming Zhang,et al. Towards Domain-agnostic Depth Completion[J]. Machine Intelligence Research,2024,21(4):652-669. |
APA | Guangkai Xu., Wei Yin., Jianming Zhang., Oliver Wang.,Simon Niklaus.,...& Jia-Wang Bian.(2024).Towards Domain-agnostic Depth Completion.Machine Intelligence Research,21(4),652-669. |
MLA | Guangkai Xu,et al."Towards Domain-agnostic Depth Completion".Machine Intelligence Research 21.4(2024):652-669. |
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