Update README.md

README.md

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 ---
 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](https://arxiv.org/abs/2303.04634)"__.
+Original GitHub implementation at [](https://github.com/perceivelab/trf-sg2im).
+
+![teaser](docs/teaser.gif)
+
+## 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.
+
+![architecture](docs/architecture.png)
+
+## Usage
+For usage instructions, please refer to the original [GitHub repo](https://github.com/perceivelab/trf-sg2im).
+