# Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation 스크린샷 2021-07-04 오후 4 11 51 the Pytorch, JAX/Flax based code imlementation of this paper : https://arxiv.org/abs/2104.00677 The model gives the 3D neural scene representation (NeRF: Neural Radiances Field) estimated from a few images. Which is based on extracting the semantic information using a pre-trained visual encoder such as CLIP, a Vision Transformer Our Project is started in the HuggingFace X GoogleAI (JAX) Community Week Event. https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104 ## Hugging Face Hub Repo URL: We will also upload our project on the Hugging Face Hub Repository. [https://huggingface.co/flax-community/putting-nerf-on-a-diet/](https://huggingface.co/flax-community/putting-nerf-on-a-diet/) Our JAX/Flax implementation currently supports:
Platform Single-Host GPU Multi-Device TPU
Type Single-Device Multi-Device Single-Host Multi-Host
Training Supported Supported Supported Supported
Evaluation Supported Supported Supported Supported
## Installation ``` # Clone the repo svn export https://github.com/google-research/google-research/trunk/jaxnerf # Create a conda environment, note you can use python 3.6-3.8 as # one of the dependencies (TensorFlow) hasn't supported python 3.9 yet. conda create --name jaxnerf python=3.6.12; conda activate jaxnerf # Prepare pip conda install pip; pip install --upgrade pip # Install requirements pip install -r jaxnerf/requirements.txt # [Optional] Install GPU and TPU support for Jax # Remember to change cuda101 to your CUDA version, e.g. cuda110 for CUDA 11.0. pip install --upgrade jax jaxlib==0.1.57+cuda101 -f https://storage.googleapis.com/jax-releases/jax_releases.html # install flax and flax-transformer pip install flax transformer[flax] ``` ## Dataset Download the datasets from the [NeRF official Google Drive](https://drive.google.com/drive/folders/128yBriW1IG_3NJ5Rp7APSTZsJqdJdfc1). Please download the `nerf_synthetic.zip` and unzip them in the place you like. Let's assume they are placed under `/tmp/jaxnerf/data/`. ## How to use ``` python -m train \ --data_dir=/PATH/TO/YOUR/SCENE/DATA \ % e.g., nerf_synthetic/lego --train_dir=/PATH/TO/THE/PLACE/YOU/WANT/TO/SAVE/CHECKPOINTS \ --config=configs/CONFIG_YOU_LIKE ``` you can toggle the semantic loss by “use_semantic_loss” in cofiguration files. ## Demo [https://huggingface.co/spaces/flax-community/DietNerf-Demo](https://huggingface.co/spaces/flax-community/DietNerf-Demo) ## Our Teams | Teams | Members | |------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------| | NeRF Team | Leader : [JaeYoung Chung](https://github.com/robot0321), Members : [Stella Yang](https://github.com/codestella), [Alex Lau](https://github.com/riven314), [Haswanth Aekula](https://github.com/hassiahk), [Hyunkyu Kim](https://github.com/minus31) | | CLIP Team | Leader : [Sunghyun Kim](https://github.com/MrBananaHuman), Members : [Seunghyun Lee](https://github.com/sseung0703), [Sasikanth Kotti](https://github.com/ksasi), [Khali Sifullah](https://github.com/khalidsaifullaah) | | Cloud TPU Team | Leader : [Alex Lau](https://github.com/riven314), Members : [JaeYoung Chung](https://github.com/robot0321), [Sunghyun Kim](https://github.com/MrBananaHuman), [Aswin Pyakurel](https://github.com/masapasa) | | Project Managing | [Stella Yang](https://github.com/codestella) To Watch Our Project Progress, Please Check [Our Project Notion](https://www.notion.so/Putting-NeRF-on-a-Diet-e0caecea0c2b40c3996c83205baf870d) | ## References This project is based on “JAX-NeRF”. ``` @software{jaxnerf2020github, author = {Boyang Deng and Jonathan T. Barron and Pratul P. Srinivasan}, title = {{JaxNeRF}: an efficient {JAX} implementation of {NeRF}}, url = {https://github.com/google-research/google-research/tree/master/jaxnerf}, version = {0.0}, year = {2020}, } ``` This project is based on “JAX-NeRF”. ``` @misc{jain2021putting, title={Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis}, author={Ajay Jain and Matthew Tancik and Pieter Abbeel}, year={2021}, eprint={2104.00677}, archivePrefix={arXiv}, primaryClass={cs.CV} } ``` ## License [Apache License 2.0](https://github.com/codestella/putting-nerf-on-a-diet/blob/main/LICENSE)