Comments (13)
已经完成了,在整理代码,效果在首页上可以看到
from unboundednerfpytorch.
那什么时候发布,有计划吗
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欢迎保持关注
from unboundednerfpytorch.
恩,谢谢。
我查看blcok-nerf,觉得它是通过图像上构建loss来优化相机位姿。这和传统的通过colmap来优化相机位姿好像不太一样,你们是怎么理解的?期待你们的答复,谢谢!
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nerf的主要任务不是位姿估计。。。他是利用colmap实现的位姿来进行高分辨率的三维重建任务
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from unboundednerfpytorch.
他是借鉴了NeRF--里面的一个技术来优化渲染效果,但是位姿估计并不是NeRF的主要目的,而是一种辅助手段
from unboundednerfpytorch.
并且位姿优化并不是这篇论文里面的核心技术
from unboundednerfpytorch.
恩,你说的对。
我就是想知道它是怎么得到准确的相机位姿的,因为nerf++用了colmap,mega-nerf用了pixel-perfect-sfm来优化相机位姿。实际在我们自己的数据集上,测试发现相机位姿并不能保证准确,需要refine。
from unboundednerfpytorch.
这是nerf--的工作,你可以去了解一下,并且谷歌数据集尽管没有提供位姿数据(直接给rays也可以完成nerf),但是你可以通过一些优化方法来求得真实的位姿
from unboundednerfpytorch.
哦,多谢答复。
那你认为block-nerf是怎样得到相机位姿的呢,你了解吗?
from unboundednerfpytorch.
我问过作者,他说是用的colmap,论文里面似乎也有提,你可以去看看补充材料部分
from unboundednerfpytorch.
谢谢!
from unboundednerfpytorch.
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