trf-sg2im
Model card for the paper "Transformer-Based Image Generation from Scene Graphs". Original GitHub implementation here.
Model
This model is a two-stage scene-graph-to-image approach. It takes a scene graph as input and generates a layout using a transformer-based architecture with Laplacian Positional Encoding. Then, it uses this estimated layout to condition an autoregressive GPT-like transformer to compose the image in the latent, discrete space, converted into the final image by a VQVAE.
Usage
For usage instructions, please refer to the original GitHub repo.
Results
Comparison with other state-of-the-art approaches
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The HF Inference API does not support text-to-image models for transformers library.