论文标题
无描述符的多视图区域匹配实例3D重建
Descriptor-Free Multi-View Region Matching for Instance-Wise 3D Reconstruction
论文作者
论文摘要
本文提出了实例分割的多视图扩展，而无需依赖纹理或形状描述符匹配。对于具有重复性纹理和形状（例如植物叶）的场景，由于使用纹理或形状描述符的多视图匹配的难度，多视图实例细分变得具有挑战性。为此，我们提出了一种基于表现几何形状的多视图区域匹配方法，该方法不依赖任何特征描述符。我们进一步表明，表极区域匹配可以很容易地集成为例如分割，并且有效，以实例的3D重建。实验证明了与基线方法相比，多视图实例匹配和3D重建的精度提高了。
This paper proposes a multi-view extension of instance segmentation without relying on texture or shape descriptor matching. Multi-view instance segmentation becomes challenging for scenes with repetitive textures and shapes, e.g., plant leaves, due to the difficulty of multi-view matching using texture or shape descriptors. To this end, we propose a multi-view region matching method based on epipolar geometry, which does not rely on any feature descriptors. We further show that the epipolar region matching can be easily integrated into instance segmentation and effective for instance-wise 3D reconstruction. Experiments demonstrate the improved accuracy of multi-view instance matching and the 3D reconstruction compared to the baseline methods.
