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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

Showing 26–41 of 41 papers

TitleStatusHype
GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation—0
Image Generation from Layout—0
LTOS: Layout-controllable Text-Object Synthesis via Adaptive Cross-attention Fusions—0
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation—0
ObjBlur: A Curriculum Learning Approach With Progressive Object-Level Blurring for Improved Layout-to-Image Generation—0
Object-Centric Image Generation from Layouts—0
PlanGen: Towards Unified Layout Planning and Image Generation in Auto-Regressive Vision Language Models—0
Psi-Sampler: Initial Particle Sampling for SMC-Based Inference-Time Reward Alignment in Score Models—0
ReCo: Region-Controlled Text-to-Image Generation—0
CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation—0
DivCon: Divide and Conquer for Progressive Text-to-Image Generation—0
SmartMask: Context Aware High-Fidelity Mask Generation for Fine-grained Object Insertion and Layout Control—0
Boundary Attention Constrained Zero-Shot Layout-To-Image Generation—0
SSMG: Spatial-Semantic Map Guided Diffusion Model for Free-form Layout-to-Image Generation—0
LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation—0
Layout-to-Image Generation with Localized Descriptions using ControlNet with Cross-Attention Control—0
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