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Layout-to-Image Generation

Layout-to-image generation its the task to generate a scene based on the given layout. The layout describes the location of the objects to be included in the output image. In this section, you can find state-of-the-art leaderboards for Layout-to-image generation.

Papers

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Showing 26–41 of 41 papers

TitleStatusHype
ObjBlur: A Curriculum Learning Approach With Progressive Object-Level Blurring for Improved Layout-to-Image Generation—0
DivCon: Divide and Conquer for Progressive Text-to-Image Generation—0
Layout-to-Image Generation with Localized Descriptions using ControlNet with Cross-Attention Control—0
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation—0
SmartMask: Context Aware High-Fidelity Mask Generation for Fine-grained Object Insertion and Layout Control—0
SSMG: Spatial-Semantic Map Guided Diffusion Model for Free-form Layout-to-Image Generation—0
LAW-Diffusion: Complex Scene Generation by Diffusion with Layouts—0
GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation—0
Guided Image Synthesis via Initial Image Editing in Diffusion ModelCode0
LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation—0
ReCo: Region-Controlled Text-to-Image Generation—0
AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and StyleCode0
Generating Annotated High-Fidelity Images Containing Multiple Coherent ObjectsCode0
Object-Centric Image Generation from Layouts—0
Specifying Object Attributes and Relations in Interactive Scene GenerationCode0
Image Generation from Layout—0
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