metadata
license: apache-2.0
datasets:
- multi-train/coco_captions_1107
- visual_genome
language:
- en
pipeline_tag: text-to-image
tags:
- scene_graph
- transformers
- laplacian
- autoregressive
- vqvae
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
