This is part of my journey of learning NeRF.

2.3. Differentiable Forward Maps

Differentiable rendering

This is part of my journey of learning NeRF.

2.2. Hybrid representations

Tradeoffs of choosing a proper representation

This is part of my journey of learning NeRF.

2.1. Network Architecture

1. Input Encoding

Similar as NLP, they use position encodings. Like Sinusoid functions. I also remember an encoding method which takes into consider of the 光线的散射

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.

Contents

Learning NeRF: Reading list, learning references, and plans

Notes of CVPR22' Tutorial:

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.

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 \(hidden\_states\)?

论文地址：https://shihmengli.github.io/3D-Photo-Inpainting

作者：Meng-Li Shih, Shih-Yang Su, Johannes Kopf, Jia-Bin Huang

发表： CVPR2020

链接： https://github.com/vt-vl-lab/3d-photo-inpainting

论文地址：https://arxiv.org/abs/2112.13715

作者：Ailing Zeng, Lei Yang, Xuan Ju, Jiefeng Li, Jianyi Wang, Qiang Xu

发表： ECCV 2022

链接： https://github.com/cure-lab/SmoothNet

失眠的话

夜晚就变得绵长

第几节脊椎上了发条，拧动时

奇异的对偶的诗流向新的小节

论文地址：https://arxiv.org/abs/2203.12575

作者：Jiang, Wei and Yi, Kwang Moo and Samei, Golnoosh and Tuzel, Oncel and Ranjan, Anurag

发表： ECCV22

开源代码： https://github.com/apple/ml-neuman