Mip-NeRF是CVPR2021的工作,是对NERF的改进,主要解决了NERF的混叠、模糊问题,改进了渲染效果。[1] 论文:Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields 代码:github.com/google/mipne 原NERF paper:苏城九:NeRF ECCV2020 原始的NeRF在渲染过程中,由于是对每个像素采样一条很窄的...
Mip-NeRF算法思想。 Paper explanation Mip-NeRF360 and BlockNeRF 一、NeRF 的缺点 所有采样点都是:光心+像素中心的射线确定的,如果给定的图像分辨率比较低,那么每个像素会很大,中心点是不足以代表整个像素的颜色的;这会导致 NeRF 锯齿化太严重的问题(边缘不是直接从白到黑,而是慢慢渐变)。anti-aliasing 二、Mip...
2:在mip_nerf.py 修改代码,大概109行左右,目的是对报错的该行代码添加一个if条件,释放无关内存 view_direction=repeat(view_direction,'batchfeature->batchsamplefeature',sample=num_samples)x=torch.cat([bottleneck,view_direction],dim=-1)# if hasattr(torch.cuda, 'empty_cache'):# x = torch.cat([b...
For example, a NeRF could recreate all input images by simply reconstructing each im- 5471 age as a textured plane immediately in front of its respec- tive camera. The original NeRF paper regularized ambigu- ous scenes by injecting Gaussian noise into the density head o...
and a novel distortion-based regularizer to overcome the challenges presented by unbounded scenes. Our model, which we dub “mip-NeRF 360” as we target scenes in which the camera rotates 360 degrees around a point, reduces mean-squared error by 54% compared to mip-NeRF, and is able to ...
实现细节、单尺度blender数据集结果、真实数据集结果请参考paper原文,这里仅给出多尺度blender数据集和消融实验的实验结果。其中,Rip-NeRF ,是Rip-NeRF经过 次迭代训练的版本,完整版本经过了 次迭代。 3.1 多尺度Blender数据集上的评估 与Mip-NeRF和Tri-MipRF一样,为了评估渲染抗锯齿和精细图像细节的能力,我们在多尺...
Additional Model Details Our model contains some small components not dis- cussed in the main paper that improve performance slightly. Off-Axis Positional Encoding. When constructing inte- grated positional encoding features, we must select a ba- sis P. In mip-NeRF [1], this basis is...
paper Info: https://arxiv.org/abs/2307.11335 code: https://github.com/wbhu/Tri-MipRF Summary Tri-MipRF是另一篇改进fundamental representation的工作,它把mip-nerf跟tri-plane结合起来,这个工作的训练速度很快,且渲染效果也很不错,甚至在RTX 3090上可以达到实时渲染的程度。
Example scripts for training mip-NeRF on individual scenes from the three datasets used in the paper can be found inscripts/. You'll need to change the paths to point to wherever the datasets are located.Ginconfiguration files for our model and some ablations can be found inconfigs/. An ...
Tanks and Temples, as processed by the NeRF++ paper Tanks and Temples, as processed by the Free View Synthesis paper The main data loader we rely on isLLFF(named for historical reasons), which is the loader for a dataset that has been posed by COLMAP. ...