DreamView

Official PyTorch implementation of paper “DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation”.

This repository currently only includes the inference code for text-to-image generation (DreamView-2D). The remaining code, such as the training script and 3D generation, will be released in two months.

You can check DreamView-2D/ for the text-to-image generation code.

News

• 2024/4/11: We release the inference code of DreamView-2D, and the DreamView checkpoint: Baidu Drive, Google Drive, ModelScope, HuggingFace
• 2024/4/10: Our arxiv paper can be found here

TODO

• Release the rendered dataset
• Release the code of DreamView-3D
• Release the training script for training DreamView-2D

Preliminary

Environment

• For DreamView-2D: please follow MVDream to prepare the environments
• For DreamView-3D: TBD...

We also provide our environment for reference, as shown in DreamView-2D/env-DreamView-2D.txt

Checkpoint

• Download the checkpoints at Baidu Drive, Google Drive, ModelScope, HuggingFace
• Move the checkpoints to ckpts/

Text-to-image Generation

Inference

Running the below script

cd DreamView-2D
python t2i.py --num_samples 4 --fp16

and you are expected to obtain the below result: It takes about 10G GPU memory to run the text-to-image generation, and you can modify the DreamView-2D/t2i.py to generate your own content.

Training

TBD...

Text-to-3D Generation

TBD...

If you have any problem, feel free to open an issue or contact me :-)

Acknowledgement

• The repository of DreamView-2d is heavily based on MVDream and Stable Diffusion.
• We would like to thank the authors for sharing their exciting works.

Citation

• If you find this repo helpful, please consider citing us:

@article{yan2024DreamView,
  author = {Yan, Junkai and Gao, Yipeng and Yang, Qize and Wei, Xihan and Xie, Xuansong and Wu, Ancong and Zheng, Wei-Shi},
  title = {DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation},
  journal = {arXiv},
  year = {2024}
}