Neural Sparse Voxel Fields 在本节中,我们将介绍神经稀疏体素场 (NSVF),这是一种将神经隐式场与显式稀疏体素结构相结合的混合场景表示。 NSVF 不是将整个场景表示为单个隐式场,而是由一组以稀疏体素八叉树组织的体素有界隐式场组成。 在下文中,我们描述了 NSVF 的构建块 - 一个体素有界隐式场(第 3.1 节) - 随后是 N
NSVF is MIT-licensed. The license applies to the pre-trained models as well. Please cite as @article{liu2020neural,title={Neural Sparse Voxel Fields},author={Liu, Lingjie and Gu, Jiatao and Lin, Kyaw Zaw and Chua, Tat-Seng and Theobalt, Christian},journal={NeurIPS},year={2020}}...
AI论文探讨室·A+·第101期-Neural Sparse Voxel Fields(神经稀疏体素化场),使用经典的计算机图形技术合成真实世界图像级视点图像是非常困难的,因为它捕获外观细节和几何模型是非
通过诸如八叉树或包围体层次结构这样的层次数据结构来加速光线追踪的想法在渲染文献中已有深入研究,不过这些方法假定事先知道场景的几何形状,因此不能自然地推广到场景几何形状未知且必须恢复的逆向渲染环境中。实际上,尽管在优化类NeRF模型时构建了八叉树加速结构,神经稀疏体素场(Neural Sparse Voxel Fields)方法并没有...
Neural sparse voxel fields. NeurIPS, 2020. 2 [26] Subhransu Maji, Alexander C Berg, and Jitendra Malik. Classification using intersection kernel support vector ma- chines is efficient. CVPR, 2008. 5 [27] Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi, Jo...
在位姿优化领域，BARF与ViewFormer分别从不同角度利用INR技术提升效率。BARF采用神经辐射场来优化相机位姿，而ViewFormer则利用Transformer解决仅基于少量图像的神经渲染问题。此外，Neural Sparse Voxel Fields与pixelNeRF也分别通过使用特征网格与像素级神经辐射场，进一步探索INR在SLAM应用的可能性。在三维场景重建...
Barf: Bundle-adjusting neural radi- ance fields. In Proceedings of the IEEE/CVF Interna- tional Conference on Computer Vision, pages 5741– 5751, 2021. [24] Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt. Neural sparse voxel fields. Advances in Neu...
Indeed, despite building an octree acceleration structure while optimizing a NeRF-like model, the Neural Sparse Voxel Fields approach does not significantly reduce training time [28].Ambiguity. Though NeRFs are traditionally optimized using many input images of a scene, the problem of recovering a ...
Neural Sparse Voxel Fields,NeurIPS 2020 NSVF这篇工作针对传统nerf由于网络capacity不足会导致一些细节丢失的问题,提出使用一个sparse voxel octree,其中每个cell侧重对局部区域建模,在render时也可以跳过空的cell,从而加速渲染。 整个场景被表示成一些稀疏的voxel,vexel的顶点保存feature,voxel内的任意点的feature由8个顶...
Neural Sparse Voxel FieldsApplies a similar concept to neural radiance fields. Pixel-NERF(Yu et al. 2020) proposes to condition a NeRF on local features lying on camera rays, extracted from contact images, as proposed in PiFU (see "from 3D supervision"). ...