用多视角模糊图像同时去模糊并重建高精度3D模型
Joint Deblurring and 3D Reconstruction for Macrophotography
- 联合优化清晰3D模型与像素级模糊核
- 仅需少量图像即实现高质量去模糊与3D重建
- 适合微距摄影中需精细成像的科研与工业场景
微距镜头具有高分辨率和大放大倍数的优点，对小型精细物体进行3D建模可提供更丰富的信息。然而，微距摄影中的离焦模糊是长期存在的问题，严重阻碍了成像清晰度及高质量3D重建。传统图像去模糊方法需要大量图像和标注，且目前尚无适用于微距摄影的多视角3D重建方法。本文提出一种面向微距摄影的联合去模糊与3D重建方法。从多视角模糊图像出发，联合优化物体的清晰3D模型与每个像素的离焦模糊核。整个框架采用可微渲染方法，自监督地优化3D模型与模糊核。大量实验表明，仅需少量多视角图像，该方法即可实现高质量图像去模糊，并恢复高保真3D外观。
原文摘要 · Abstract (English)
Macro lens has the advantages of high resolution and large magnification, and 3D modeling of small and detailed objects can provide richer information. However, defocus blur in macrophotography is a long-standing problem that heavily hinders the clear imaging of the captured objects and high-quality 3D reconstruction of them. Traditional image deblurring methods require a large number of images and annotations, and there is currently no multi-view 3D reconstruction method for macrophotography. In this work, we propose a joint deblurring and 3D reconstruction method for macrophotography. Starting from multi-view blurry images captured, we jointly optimize the clear 3D model of the object and the defocus blur kernel of each pixel. The entire framework adopts a differentiable rendering method to self-supervise the optimization of the 3D model and the defocus blur kernel. Extensive experiments show that from a small number of multi-view images, our proposed method can not only achieve high-quality image deblurring but also recover high-fidelity 3D appearance.
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