Image Generation from Scene Graphs
4 papers with code • 3 benchmarks • 3 datasets
Most implemented papers
Image Generation from Scene Graphs
To overcome this limitation we propose a method for generating images from scene graphs, enabling explicitly reasoning about objects and their relationships.
MIGS: Meta Image Generation from Scene Graphs
We propose MIGS (Meta Image Generation from Scene Graphs), a meta-learning based approach for few-shot image generation from graphs that enables adapting the model to different scenes and increases the image quality by training on diverse sets of tasks.
Transformer-based Image Generation from Scene Graphs
In this work, we show how employing multi-head attention to encode the graph information, as well as using a transformer-based model in the latent space for image generation can improve the quality of the sampled data, without the need to employ adversarial models with the subsequent advantage in terms of training stability.
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph Generation
However, no current approaches in Scene Graph Generation (SGG) aim at providing useful graphs for downstream tasks.