LayoutVAE: Stochastic Scene Layout Generation from a Label Set

07/24/2019
by   Akash Abdu Jyothi, et al.
3

Recently there is an increasing interest in scene generation within the research community. However, scene layouts are largely being modeled in deterministic fashion, ignoring any plausible visual variations given the same textual description as input. We propose LayoutVAE, a variational autoencoder based framework for generating stochastic scene layouts. LayoutVAE is a versatile modeling framework that allows for generating full image layouts given a label set, or per label layouts for an existing image given a new label. In addition, it is also capable of detecting unusual layouts, potentially providing a way to evaluate layout generation problem. Extensive experiments on MNIST-Layouts and challenging COCO 2017 Panoptic dataset verifies the effectiveness of our proposed framework.

READ FULL TEXT

page 1

page 5

page 8

research
01/21/2019

LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators

Layout is important for graphic design and scene generation. We propose ...
research
07/23/2020

End-to-End Optimization of Scene Layout

We propose an end-to-end variational generative model for scene layout s...
research
05/05/2022

Scene Graph Expansion for Semantics-Guided Image Outpainting

In this paper, we address the task of semantics-guided image outpainting...
research
09/02/2019

Relationship-Aware Spatial Perception Fusion for Realistic Scene Layout Generation

The significant progress on Generative Adversarial Networks (GANs) have ...
research
10/29/2021

Polyline Based Generative Navigable Space Segmentation for Autonomous Visual Navigation

Detecting navigable space is a fundamental capability for mobile robots ...
research
08/19/2019

Seq-SG2SL: Inferring Semantic Layout from Scene Graph Through Sequence to Sequence Learning

Generating semantic layout from scene graph is a crucial intermediate ta...
research
12/10/2021

Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms

Realistic 3D indoor scene datasets have enabled significant recent progr...

Please sign up or login with your details

Forgot password? Click here to reset