Genwarp models are the official checkpoints for ther paper "GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping". Genwarp can generate novel view images from a single input conditioned on camera poses. In this repository, we offer the codes for inference of the model. For detailed information, please refer to the paper.
The model is intended for research purposes only. Possible research areas and tasks include
Excluded uses are described below.
Note: This section is taken from the CreativeML Open RAIL-M Genwarp models.
Use Restrictions
You agree not to use the Model or Derivatives of the Model:
For use-cases and examples, follow the instructions here
Training Data The model developers used the following dataset for training the model:
Training Procedure
Genwarp models are finetuned based on Stable Diffusion v1-5.
For more details, please refer to the paper.
Please refer to the paper.
@article{seo2024genwarp,
title={GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping},
author={Junyoung Seo and Kazumi Fukuda and Takashi Shibuya and Takuya Narihira and Naoki Murata and Shoukang Hu and Chieh-Hsin Lai and Seungryong Kim and Yuki Mitsufuji},
year={2024},
journal={arXiv preprint arXiv:2405.17251}
}
Genwarp models are the official checkpoints for ther paper "GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping". Genwarp can generate novel view images from a single input conditioned on camera poses. In this repository, we offer the codes for inference of the model. For detailed information, please refer to the paper.
The model is intended for research purposes only. Possible research areas and tasks include
Excluded uses are described below.
Note: This section is taken from the CreativeML Open RAIL-M Genwarp models.
Use Restrictions
You agree not to use the Model or Derivatives of the Model:
For use-cases and examples, follow the instructions here
Training Data The model developers used the following dataset for training the model:
Training Procedure
Genwarp models are finetuned based on Stable Diffusion v1-5.
For more details, please refer to the paper.
Please refer to the paper.
@article{seo2024genwarp,
title={GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping},
author={Junyoung Seo and Kazumi Fukuda and Takashi Shibuya and Takuya Narihira and Naoki Murata and Shoukang Hu and Chieh-Hsin Lai and Seungryong Kim and Yuki Mitsufuji},
year={2024},
journal={arXiv preprint arXiv:2405.17251}
}