Runjia Li1, Junlin Han1, Luke Melas-Kyriazi1, Chunyi Sun2, Zhaochong An3, Zhongrui Gui1, Shuyang Sun1, Philip Torr1, Tomas Jakab1
1University of Oxford, 2Australian National University, 3University of Copenhagen
- We introduce DreamBeast, a new method for generating part-aware 3D assets efficiently.
- Utilize a novel part-aware knowledge transfer mechanism.
- Efficiently extract part-level knowledge from Stable Diffusion 3 into a Part-Affinity NeRF for instant generation from various camera views.
- Render Part-Affinity maps from the Part-Affinity NeRF and modulate a multi-view diffusion model during score distillation sampling (SDS).
- Improves the part-awareness and quality of generated 3D creatures with efficient computational costs.
The DreamBeast extension for threestudio. To use it, simply install this extension in threestudio custom
directory.
cd custom
git clone https://github.com/runjiali-rl/threestudio-dreambeast.git
cd threestudio-dreambeast
# First install xformers (https://github.com/facebookresearch/xformers#installing-xformers)
# cuda 11.8 version
pip3 install -U xformers --index-url https://download.pytorch.org/whl/cu118
# cuda 12.1 version
pip3 install -U xformers --index-url https://download.pytorch.org/whl/cu121
# Then install other dependencies
pip install -r requirements.txt
# Run the following commands in the threestudio repository
# Replace the OPENAI_API_KEY with your openai api key
python launch.py --config custom/threestudio-dreambeast/configs/dreambeast.yaml --train --gpu 0 system.prompt_processor.prompt="a creature with a body of a kangaroo and the shell of a tortoise" "system.api_key=OPENAI_API_KEY",
python launch.py --config custom/threestudio-dreambeast/configs/dreambeast.yaml --train --gpu 0 system.prompt_processor.prompt="a car with airplane wings" "system.api_key=OPENAI_API_KEY",
python launch.py --config custom/threestudio-dreambeast/configs/dreambeast.yaml --train --gpu 0 system.prompt_processor.prompt="An object with the screen of a television and the wings of a butterfly" "system.api_key=OPENAI_API_KEY",
If you find DreamBeast helpful, please consider citing:
@misc{li2024dreambeastdistilling3dfantastical,
title={DreamBeast: Distilling 3D Fantastical Animals with Part-Aware Knowledge Transfer},
author={Runjia Li and Junlin Han and Luke Melas-Kyriazi and Chunyi Sun and Zhaochong An and Zhongrui Gui and Shuyang Sun and Philip Torr and Tomas Jakab},
year={2024},
eprint={2409.08271},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2409.08271},
}