[going_ham]

NeRFs are cool technology that has its place and use. It is going to help with scene reconstruction and so on. And that is the reason why these CV researchers are flocking into using it. Despite knowing the limitations, they are giving their best to improve this technology. What I believe is NeRF is insufficient to be meaningful on its own. If you look into the architecture from this problem (the paper in the post), it clearly shows that they have some refinement phase going later on. A single RGB 2D to 3D model is such an ill-posed, we have to consider a lot of priors before diving into it.

There needs to be more foundational work in this field that can outperform or even improve the NeRF-based techniques. And the current herd mentality of researchers should be changed into exploring the alternatives. There is a reason why expensive automobile companies still rely on the physical modelling of their design. It's hard to simulate the physical conditions only through CAD modelling. Sure NeRFs are cool and they can make impressive results. That doesn't necessarily mean it is the means to an end. Look where rasterization brought us! NeRF is like rasterization. It is going to be used. But highly quality graphics was possible through GI and ray tracing! NeRF needs something equivalent that is physically grounded.

[milkey_mouse]

> NeRF needs something equivalent that is physically grounded.

Have you seen Plenoxels? https://alexyu.net/plenoxels/