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CODE_OF_CONDUCT.md

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+# Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to make 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.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+* 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
+
+Examples of unacceptable behavior by participants include:
+
+* The use of sexualized language or imagery and unwelcome sexual attention or
+  advances
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+* Public or private harassment
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+* Other conduct which could reasonably be considered inappropriate in a
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+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
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+
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+
+## Scope
+
+This Code of Conduct applies within all project spaces, and it also applies when
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+
+This Code of Conduct also applies outside the project spaces when there is a
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+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
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+Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
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+members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see
+https://www.contributor-covenant.org/faq

CONTRIBUTING.md

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+# Contributing to PoseDiffusion
+We want to make contributing to this project as easy and transparent as
+possible.
+
+## Pull Requests
+We actively welcome your pull requests.
+
+1. Fork the repo and create your branch from `main`.
+2. If you've added code that should be tested, add tests.
+3. If you've changed APIs, update the documentation.
+4. Ensure the test suite passes.
+5. Make sure your code lints.
+6. If you haven't already, complete the Contributor License Agreement ("CLA").
+
+## Contributor License Agreement ("CLA")
+In order to accept your pull request, we need you to submit a CLA. You only need
+to do this once to work on any of Facebook's open source projects.
+
+Complete your CLA here: <https://code.facebook.com/cla>
+
+## Issues
+We use GitHub issues to track public bugs. Please ensure your description is
+clear and has sufficient instructions to be able to reproduce the issue.
+
+Facebook has a [bounty program](https://www.facebook.com/whitehat/) for the safe
+disclosure of security bugs. In those cases, please go through the process
+outlined on that page and do not file a public issue.
+
+## License
+By contributing to PoseDiffusion, you agree that your contributions will be licensed
+under the LICENSE file in the root directory of this source tree.

LICENSE

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README.md

@@ -1,3 +1,112 @@
----
-license: cc-by-nc-nd-4.0
----
+---
+license: cc-by-nc-2.0
+pipeline_tag: image-to-3d
+---
+# [ECCV 2024] VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models
+
+[Porject page](https://junlinhan.github.io/projects/vfusion3d.html), [Paper link](https://arxiv.org/abs/2403.12034)
+
+VFusion3D is a large, feed-forward 3D generative model trained with a small amount of 3D data and a large volume of synthetic multi-view data. It is the first work exploring scalable 3D generative/reconstruction models as a step towards a 3D foundation.
+
+[VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models](https://junlinhan.github.io/projects/vfusion3d.html)<br>
+[Junlin Han](https://junlinhan.github.io/), [Filippos Kokkinos](https://www.fkokkinos.com/), [Philip Torr](https://www.robots.ox.ac.uk/~phst/)<br>
+GenAI, Meta and TVG, University of Oxford<br>
+European Conference on Computer Vision (ECCV), 2024
+
+
+## News
+
+- [08.08.2024] [HF Demo](https://huggingface.co/spaces/facebook/VFusion3D) is available, big thanks to [Jade Choghari](https://github.com/jadechoghari)'s help for making it possible. 
+- [25.07.2024] Release weights and inference code for VFusion3D.
+
+
+
+## Quick Start
+
+Getting started with VFusion3D is super easy! 🤗 Here’s how you can use the model with Hugging Face:
+
+### Install Dependencies (Optional)
+
+Depending on your needs, you may want to enable specific features like mesh generation or video rendering. We've got you covered with these additional packages:
+
+```bash
+!pip --quiet install imageio[ffmpeg] PyMCubes trimesh rembg[gpu,cli] kiui
+```
+
+### Load model directly
+```python
+import torch
+from transformers import AutoModel, AutoProcessor
+
+# load the model and processor
+model = AutoModel.from_pretrained("jadechoghari/vfusion3d", trust_remote_code=True)
+processor = AutoProcessor.from_pretrained("jadechoghari/vfusion3d")
+
+# download and preprocess the image
+import requests
+from PIL import Image
+from io import BytesIO
+
+image_url = 'https://sm.ign.com/ign_nordic/cover/a/avatar-gen/avatar-generations_prsz.jpg'
+response = requests.get(image_url)
+image = Image.open(BytesIO(response.content))
+
+# preprocess the image and get the source camera 
+image, source_camera = processor(image)
+
+
+# generate planes (default output)
+output_planes = model(image, source_camera)
+print("Planes shape:", output_planes.shape)
+
+# generate a 3D mesh
+output_planes, mesh_path = model(image, source_camera, export_mesh=True)
+print("Planes shape:", output_planes.shape)
+print("Mesh saved at:", mesh_path)
+
+# Generate a video
+output_planes, video_path = model(image, source_camera, export_video=True)
+print("Planes shape:", output_planes.shape)
+print("Video saved at:", video_path)
+
+```
+- **Default (Planes):** By default, VFusion3D outputs planes—ideal for further 3D operations.
+- **Export Mesh:** Want a 3D mesh? Just set `export_mesh=True`, and you'll get a `.obj` file ready to roll. You can also customize the mesh resolution by adjusting the `mesh_size` parameter.
+- **Export Video:** Fancy a 3D video? Set `export_video=True`, and you'll receive a beautifully rendered video from multiple angles. You can tweak `render_size` and `fps` to get the video just right.
+
+Check out our [demo app](https://huggingface.co/spaces/facebook/VFusion3D) to see VFusion3D in action! 🤗
+
+## Results and Comparisons
+
+### 3D Generation Results
+<img src='assets/gif1.gif' width=950>
+
+<img src='assets/gif2.gif' width=950>
+
+### User Study Results
+<img src='assets/user.png' width=950>
+
+
+
+## Acknowledgement
+
+- This inference code of VFusion3D heavily borrows from [OpenLRM](https://github.com/3DTopia/OpenLRM).
+
+## Citation
+
+If you find this work useful, please cite us:
+
+
+```
+@article{han2024vfusion3d,
+  title={VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models},
+  author={Junlin Han and Filippos Kokkinos and Philip Torr},
+  journal={European Conference on Computer Vision (ECCV)},
+  year={2024}
+}
+```
+
+## License
+
+- The majority of VFusion3D is licensed under CC-BY-NC, however portions of the project are available under separate license terms: OpenLRM as a whole is licensed under the Apache License, Version 2.0, while certain components are covered by NVIDIA's proprietary license.
+- The model weights of VFusion3D is also licensed under CC-BY-NC.

__init__.py

@@ -0,0 +1,27 @@
+from transformers import AutoProcessor
+from .modeling import LRMGenerator, LRMGeneratorConfig
+
+import logging
+
+# we set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# helper function to install packages
+def install_package(package_name):
+    if importlib.util.find_spec(package_name) is None:
+        logger.info(f"Package '{package_name}' not found. Installing...")
+        print(f"Package '{package_name}' not found. Installing...")
+        subprocess.check_call([sys.executable, "-m", "pip", "install", package_name])
+    else:
+        logger.info(f"Package '{package_name}' is already installed.")
+
+# list of packages to ensure are installed
+required_packages = [
+    'imageio[ffmpeg]', 'PyMCubes', 'trimesh', 'rembg[gpu,cli]', 'kiui', 'torchvision', 'Pillow'
+]
+
+for package in required_packages:
+    install_package(package)
+
+from .processor import LRMImageProcessor

config.json

@@ -0,0 +1,27 @@
+{
+  "architectures": [
+    "LRMGenerator"
+  ],
+  "model_type": "lrm_generator",
+  "model_name_or_path": "jadechoghari/vfusion3d",
+  "camera_embed_dim": 1024,
+  "encoder_feat_dim": 768,
+  "encoder_freeze": false,
+  "encoder_model_name": "facebook/dinov2-base",
+  "model_type": "lrm_generator",
+  "rendering_samples_per_ray": 128,
+  "torch_dtype": "float32",
+  "transformer_dim": 1024,
+  "transformer_heads": 16,
+  "transformer_layers": 16,
+  "transformers_version": "4.42.4",
+  "triplane_dim": 80,
+  "triplane_high_res": 64,
+  "triplane_low_res": 32,
+  "auto_map": {
+    "AutoConfig": "modeling.LRMGeneratorConfig",
+    "AutoModel": "modeling.LRMGenerator",
+    "AutoImageProcessor": "processor.LRMImageProcessor"
+  },
+  "preprocessor_class": "LRMImageProcessor"
+}