I am currently burying myself into the sea of NeRF. I plan to archive my learning notes here. I am still a beginner, so the notes absolutely contain errors, and are not finished yet.


Learning NeRF: Reading list, learning references, and plans

Notes of CVPR22' Tutorial:

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This is part of my journey of learning NeRF.

2.4. Prior-based reconstruction of neural fields

Sounds like a one-shot task: instead of fitting and optimizing a neural field each for one scene; let's learn a prior distribution of neural field. Then, given a specific scene, it adjusts the neural field in just one forward.

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Reference: https://stackoverflow.com/questions/48302810/whats-the-difference-between-hidden-and-output-in-pytorch-lstm

I was so confused when doing a homework on implementing the Luong Attention, because it tells that the decoder is a RNN, which takes \(y_{t-1}\) and \(s_{t-1}\) as input, and outputs \(s_t\), i.e., \(s_t = RNN(y_{t-1}, s_{t-1})\).

But the pytorch implementation of RNN is: \(outputs, hidden\_last = RNN(inputs, hidden\_init)\), which takes in a sequence of elements, computes in serials, and outputs a sequence also.

I was confused about what is the \(s_t\). Is it the \(outputs\), or the \(hidden\_states\)?

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According to https://dev.to/rubberduck/using-usb-with-docker-for-mac-3fdd, it seems impossible to forward USB to a Docker container on MacOS, coz the Docker is running in a virtual environment via hyperkit.

First of all, ports of the host (i.e., MacOS) cannot be directly accessed by any virtual environment (i.e., Docker) on it. So, "you first have to expose it to the virtual machine where Docker is running". However, Docker is running on hyperkit, which doesn't support usb forwarding.

The author provided another way to do it, that is to usedocker-machine, which uses a Virtualbox VM to host the dockerd daemon, to replace the original docker. Then... why bother still using Docker, instead of just using Virtualbox to run the seperated environment?