Layout-to-Image Generation

8 papers with code • 6 benchmarks • 3 datasets

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.

Greatest papers with code

Image Generation from Scene Graphs

google/sg2im CVPR 2018

To overcome this limitation we propose a method for generating images from scene graphs, enabling explicitly reasoning about objects and their relationships.

Layout-to-Image Generation

Semantic Image Manipulation Using Scene Graphs

he-dhamo/simsg CVPR 2020

In our work, we address the novel problem of image manipulation from scene graphs, in which a user can edit images by merely applying changes in the nodes or edges of a semantic graph that is generated from the image.

Image Inpainting Image Manipulation +1

Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesis

WillSuen/LostGANs 25 Mar 2020

This paper focuses on a recent emerged task, layout-to-image, to learn generative models that are capable of synthesizing photo-realistic images from spatial layout (i. e., object bounding boxes configured in an image lattice) and style (i. e., structural and appearance variations encoded by latent vectors).

Layout-to-Image Generation

Image Synthesis From Reconfigurable Layout and Style

WillSuen/LostGANs ICCV 2019

Despite remarkable recent progress on both unconditional and conditional image synthesis, it remains a long-standing problem to learn generative models that are capable of synthesizing realistic and sharp images from reconfigurable spatial layout (i. e., bounding boxes + class labels in an image lattice) and style (i. e., structural and appearance variations encoded by latent vectors), especially at high resolution.

Layout-to-Image Generation

Learning Canonical Representations for Scene Graph to Image Generation

roeiherz/CanonicalSg2Im ECCV 2020

Generating realistic images of complex visual scenes becomes challenging when one wishes to control the structure of the generated images.

Layout-to-Image Generation Scene Generation

Context-Aware Layout to Image Generation with Enhanced Object Appearance

wtliao/layout2img CVPR 2021

We argue that these are caused by the lack of context-aware object and stuff feature encoding in their generators, and location-sensitive appearance representation in their discriminators.

Layout-to-Image Generation

Generating Annotated High-Fidelity Images Containing Multiple Coherent Objects

Cynetics/MSGNet 22 Jun 2020

In particular, layout-to-image generation models have gained significant attention due to their capability to generate realistic complex images containing distinct objects.

Layout-to-Image Generation