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# Code of Conduct | ||
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## Our Pledge | ||
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In the interest of fostering an open and welcoming environment, we as | ||
contributors and maintainers pledge to making participation in our project and | ||
our community a harassment-free experience for everyone, regardless of age, body | ||
size, disability, ethnicity, sex characteristics, gender identity and expression, | ||
level of experience, education, socio-economic status, nationality, personal | ||
appearance, race, religion, or sexual identity and orientation. | ||
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## Our Standards | ||
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Examples of behavior that contributes to creating a positive environment | ||
include: | ||
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* Using welcoming and inclusive language | ||
* Being respectful of differing viewpoints and experiences | ||
* Gracefully accepting constructive criticism | ||
* Focusing on what is best for the community | ||
* Showing empathy towards other community members | ||
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Examples of unacceptable behavior by participants include: | ||
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* The use of sexualized language or imagery and unwelcome sexual attention or | ||
advances | ||
* Trolling, insulting/derogatory comments, and personal or political attacks | ||
* Public or private harassment | ||
* Publishing others' private information, such as a physical or electronic | ||
address, without explicit permission | ||
* Other conduct which could reasonably be considered inappropriate in a | ||
professional setting | ||
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## Our Responsibilities | ||
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Project maintainers are responsible for clarifying the standards of acceptable | ||
behavior and are expected to take appropriate and fair corrective action in | ||
response to any instances of unacceptable behavior. | ||
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Project maintainers have the right and responsibility to remove, edit, or | ||
reject comments, commits, code, wiki edits, issues, and other contributions | ||
that are not aligned to this Code of Conduct, or to ban temporarily or | ||
permanently any contributor for other behaviors that they deem inappropriate, | ||
threatening, offensive, or harmful. | ||
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## Scope | ||
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This Code of Conduct applies within all project spaces, and it also applies when | ||
an individual is representing the project or its community in public spaces. | ||
Examples of representing a project or community include using an official | ||
project e-mail address, posting via an official social media account, or acting | ||
as an appointed representative at an online or offline event. Representation of | ||
a project may be further defined and clarified by project maintainers. | ||
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## Enforcement | ||
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Instances of abusive, harassing, or otherwise unacceptable behavior may be | ||
reported by contacting the open source team at [[email protected]](mailto:[email protected]). All | ||
complaints will be reviewed and investigated and will result in a response that | ||
is deemed necessary and appropriate to the circumstances. The project team is | ||
obligated to maintain confidentiality with regard to the reporter of an incident. | ||
Further details of specific enforcement policies may be posted separately. | ||
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Project maintainers who do not follow or enforce the Code of Conduct in good | ||
faith may face temporary or permanent repercussions as determined by other | ||
members of the project's leadership. | ||
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## Attribution | ||
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This Code of Conduct is adapted from the [Contributor Covenant](https://www.contributor-covenant.org), version 1.4, | ||
available at [https://www.contributor-covenant.org/version/1/4/code-of-conduct.html](https://www.contributor-covenant.org/version/1/4/code-of-conduct.html) |
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# Contribution Guide | ||
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Thanks for your interest in contributing. This project was released to accompany a research paper for purposes of reproducability, and beyond its publication there are limited plans for future development of the repository. | ||
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While we welcome new pull requests and issues please note that our response may be limited. Forks and out-of-tree improvements are strongly encouraged. | ||
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## Before you get started | ||
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By submitting a pull request, you represent that you have the right to license your contribution to Apple and the community, and agree by submitting the patch that your contributions are licensed under the [LICENSE](LICENSE). | ||
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We ask that all community members read and observe our [Code of Conduct](CODE_OF_CONDUCT.md). |
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Copyright (C) 2022 Apple Inc. All Rights Reserved. | ||
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IMPORTANT: This Apple software is supplied to you by Apple | ||
Inc. ("Apple") in consideration of your agreement to the following | ||
terms, and your use, installation, modification or redistribution of | ||
this Apple software constitutes acceptance of these terms. If you do | ||
not agree with these terms, please do not use, install, modify or | ||
redistribute this Apple software. | ||
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In consideration of your agreement to abide by the following terms, and | ||
subject to these terms, Apple grants you a personal, non-exclusive | ||
license, under Apple's copyrights in this original Apple software (the | ||
"Apple Software"), to use, reproduce, modify and redistribute the Apple | ||
Software, with or without modifications, in source and/or binary forms; | ||
provided that if you redistribute the Apple Software in its entirety and | ||
without modifications, you must retain this notice and the following | ||
text and disclaimers in all such redistributions of the Apple Software. | ||
Neither the name, trademarks, service marks or logos of Apple Inc. may | ||
be used to endorse or promote products derived from the Apple Software | ||
without specific prior written permission from Apple. Except as | ||
expressly stated in this notice, no other rights or licenses, express or | ||
implied, are granted by Apple herein, including but not limited to any | ||
patent rights that may be infringed by your derivative works or by other | ||
works in which the Apple Software may be incorporated. | ||
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The Apple Software is provided by Apple on an "AS IS" basis. APPLE | ||
MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION | ||
THE IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY AND FITNESS | ||
FOR A PARTICULAR PURPOSE, REGARDING THE APPLE SOFTWARE OR ITS USE AND | ||
OPERATION ALONE OR IN COMBINATION WITH YOUR PRODUCTS. | ||
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IN NO EVENT SHALL APPLE BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL | ||
OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF | ||
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS | ||
INTERRUPTION) ARISING IN ANY WAY OUT OF THE USE, REPRODUCTION, | ||
MODIFICATION AND/OR DISTRIBUTION OF THE APPLE SOFTWARE, HOWEVER CAUSED | ||
AND WHETHER UNDER THEORY OF CONTRACT, TORT (INCLUDING NEGLIGENCE), | ||
STRICT LIABILITY OR OTHERWISE, EVEN IF APPLE HAS BEEN ADVISED OF THE | ||
POSSIBILITY OF SUCH DAMAGE. | ||
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------------------------------------------------------------------------------- | ||
SOFTWARE DISTRIBUTED WITH ML-NEUMAN: | ||
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The ml-neuman software includes a number of subcomponents with separate | ||
copyright notices and license terms - please see the file ACKNOWLEDGEMENTS. | ||
------------------------------------------------------------------------------- |
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## NeuMan: Neural Human Radiance Field from a Single Video | ||
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This repository is a reference implementation for NeuMan. NeuMan reconstructs both the background scene and an animatable human from a single video using neural radiance fields. | ||
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[[Paper]](https://arxiv.org/abs/2203.12575) | ||
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<p align="center"> | ||
<img src="./resources/teaser.gif" height="260"> | ||
</p> | ||
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### Video demos | ||
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Novel view and novel pose synthesis | ||
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[[Bike]](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/bike.mp4) | ||
[[Citron]](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/citron.mp4) | ||
[[Parking lot]](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/demo3.mp4) | ||
[[Jogging]](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/jogging.mp4) | ||
[[Lab]](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/lab.mp4) | ||
[[Seattle]](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/seattle.mp4) | ||
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Compositional Synthesis | ||
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[[Handshake]](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/handshake.mp4) | ||
[[Dance]](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/dance.mp4) | ||
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### Environment | ||
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To create the environment using Conda: | ||
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```sh | ||
conda env create -f environment.yml | ||
``` | ||
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Alternately, you can create the environment by executing: | ||
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```sh | ||
conda create -n neuman_env python=3.7 -y; | ||
conda activate neuman_env; | ||
conda install pytorch==1.8.0 torchvision==0.9.0 cudatoolkit=10.2 -c pytorch; | ||
conda install -c fvcore -c iopath -c conda-forge fvcore iopath; | ||
conda install -c bottler nvidiacub; | ||
conda install pytorch3d -c pytorch3d; | ||
conda install -c conda-forge igl; | ||
pip install opencv-python joblib open3d imageio tensorboardX chumpy lpips scikit-image ipython matplotlib; | ||
``` | ||
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Notice that `pytorch3d` requires a specific version of pytorch, in our case `pytorch=1.8.0`. | ||
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Activate the environment: | ||
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```sh | ||
conda activate neuman_env | ||
``` | ||
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### Demo | ||
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- Download SMPL weights: | ||
- Registration is required to download the UV map(Download UV map in OBJ format) from [SMPL](https://smpl.is.tue.mpg.de/download.php). | ||
- Download neutral SMPL weights(SMPLIFY_CODE_V2.ZIP) from [SMPLify](https://smplify.is.tue.mpg.de/download.php), extract `basicModel_neutral_lbs_10_207_0_v1.0.0.pkl` and rename it to `SMPL_NEUTRAL.pkl`. | ||
- Put the all the downloaded files into `./data/smplx` folder with following structure: | ||
```bash | ||
. | ||
└── data | ||
└── smplx | ||
├── smpl | ||
│ └── SMPL_NEUTRAL.pkl | ||
└── smpl_uv.obj | ||
``` | ||
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- Download NeuMan dataset and pretrained models: | ||
- Data ([download](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/dataset.zip)) | ||
- Pretrained models ([download](https://docs-assets.developer.apple.com/ml-research/datasets/neuman/pretrained.zip)) | ||
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Alternately, run the following script to set up data and pretrained models. | ||
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```sh | ||
bash setup_data_and_models.sh | ||
``` | ||
- (*Optional*) Download AMASS dataset for reposing: | ||
- AMASS dataset is used for rendering novel poses, specifically `render_reposing.py` and `render_gathering.py`. | ||
- We used SFU mocap(SMPL+H G) subset, please download from [AMASS](https://amass.is.tue.mpg.de/download.php). | ||
- Put the downloaded mocap data in to `./data/SFU` folder. | ||
```bash | ||
. | ||
└── data | ||
└── SFU | ||
├── 0005 | ||
├── 0007 | ||
│ ... | ||
└── 0018 | ||
``` | ||
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- Render using pretrained model | ||
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Render 360 views of a human: | ||
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```sh | ||
python render_360.py --scene_dir ./data/bike --weights_path ./out/bike_human/checkpoint.pth.tar --mode canonical_360 | ||
``` | ||
Render test views of a sequence, and evaluate the metrics: | ||
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```sh | ||
python render_test_views.py --scene_dir ./data/bike --weights_path ./out/bike_human/checkpoint.pth.tar | ||
``` | ||
Render novel poses with the background: | ||
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```sh | ||
python render_reposing.py --scene_dir ./data/bike --weights_path ./out/bike_human/checkpoint.pth.tar --motion_name=jumpandroll | ||
``` | ||
Render telegathering: | ||
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```sh | ||
python render_gathering.py --actors parkinglot seattle citron --scene_dir ./data/seattle --weights_path ./out/seattle_human/checkpoint.pth.tar | ||
``` | ||
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### Training | ||
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- Download NeuMan dataset | ||
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- Train scene NeRF | ||
```sh | ||
python train.py --scene_dir ./data/bike/ --name=bike_background --train_mode=bkg | ||
``` | ||
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- Train human NeRF | ||
```sh | ||
python train.py --scene_dir ./data/bike --name=bike_human --load_background=bike_background --train_mode=smpl_and_offset | ||
``` | ||
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### Use your own video | ||
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- Preprocess: Check [preprocess](./preprocess/README.md) | ||
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### Citation | ||
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``` | ||
@inproceedings{jiang2022neuman, | ||
title={NeuMan: Neural Human Radiance Field from a Single Video}, | ||
author={Jiang, Wei and Yi, Kwang Moo and Samei, Golnoosh and Tuzel, Oncel and Ranjan, Anurag}, | ||
booktitle={Proceedings of the European conference on computer vision (ECCV)}, | ||
year={2022} | ||
} | ||
``` | ||
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### License | ||
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The code is released under the [LICENSE](./LICENSE) terms. |
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