tgokhale/sr2d_visor

Benchmarking Spatial Relationships in Text-to-Image Generation

Tejas Gokhale, Hamid Palangi, Besmira Nushi, Vibhav Vineet, Eric Horvitz, Ece Kamar, Chitta Baral, Yezhou Yang

• We introduce a large-scale challenge dataset SR_2D that contains sentences describing two objects and the spatial relationship between them.
• We introduce a metric called VISOR (short for VerifyIng Spatial Object Relationships) to quantify spatial reasoning performance.
• VISOR and SR_2D can be used off-the-shelf with any text-to-image model.

SR_2D Dataset

Our dataset is hosted as here. This contains

1. The text prompt dataset in .json format (text_spatial_rel_phrases.json)
2. Images generated using 7 models (GLIDE, CogView2, DALLE-mini, Stable Diffusion, GLIDE + Stable Diffusion + CDM, and Stable Diffusion v2.1)

Alternatively, the text prompt dataset can also accessed from text_spatial_rel_phrases.json. It contains all examples from the current version of the dataset (31680 text prompts) accompanied by the corresponding metadata. This dataset can also be generated by running the script python create_spatial_phrases.py

GitHub repository

The GitHub repository for VISOR contains code for generating images with prompts from the SR_2D dataset and evaluating the generated images using VISOR.

References

Code for text-to-image generation:

1. GLIDE: https://github.com/openai/glide-text2im
2. DALLE-mini: https://github.com/borisdayma/dalle-mini
3. CogView2: https://github.com/THUDM/CogView2
4. Stable Diffusion: https://github.com/CompVis/stable-diffusion
5. Composable Diffusion Models: https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
6. OpenAI API for DALLE-2: https://openai.com/api/

Citation

If you find SR_2D or VISOR useful in your research, please use the following citation:

@article{gokhale2022benchmarking,
  title={Benchmarking Spatial Relationships in Text-to-Image Generation},
  author={Gokhale, Tejas and Palangi, Hamid and Nushi, Besmira and Vineet, Vibhav and Horvitz, Eric and Kamar, Ece and Baral, Chitta and Yang, Yezhou},
  journal={arXiv preprint arXiv:2212.10015},
  year={2022}
}