End-to-end Generative Floor-plan and Layout with Attributes and Relation Graph

• URL: http://arxiv.org/abs/2012.08514v1
• Date: Tue, 15 Dec 2020 07:37:05 GMT
• Title: End-to-end Generative Floor-plan and Layout with Attributes and Relation Graph
• Authors: Xinhan Di, Pengqian Yu, Danfeng Yang, Hong Zhu, Changyu Sun, YinDong Liu
• Abstract summary: We propose an end-end model for producing furniture layout for interior scene synthesis from the random vector. The proposed model combines a conditional floor-plan module of the room, a conditional graphical floor-plan module of the room and a conditional layout module. We conduct our experiments on the proposed real-world interior layout dataset that contains $191208$ designs from the professional designers.
• Score: 6.259404056725123
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose an end-end model for producing furniture layout for interior scene synthesis from the random vector. This proposed model is aimed to support professional interior designers to produce the interior decoration solutions more quickly. The proposed model combines a conditional floor-plan module of the room, a conditional graphical floor-plan module of the room and a conditional layout module. As compared with the prior work on scene synthesis, our proposed three modules enhance the ability of auto-layout generation given the dimensional category of the room. We conduct our experiments on the proposed real-world interior layout dataset that contains $191208$ designs from the professional designers. Our numerical results demonstrate that the proposed model yields higher-quality layouts in comparison with the state-of-the-art model. The dataset and code are released \href{https://github.com/CODE-SUBMIT/dataset3}{Dataset,Code}

Related papers

• Mixed Diffusion for 3D Indoor Scene Synthesis [55.94569112629208]
  We present MiDiffusion, a novel mixed discrete-continuous diffusion model architecture. We represent a scene layout by a 2D floor plan and a set of objects, each defined by its category, location, size, and orientation. Our experimental results demonstrate that MiDiffusion substantially outperforms state-of-the-art autoregressive and diffusion models in floor-conditioned 3D scene synthesis.
  arXiv  Detail & Related papers  (2024-05-31T17:54:52Z)
• I-Design: Personalized LLM Interior Designer [57.00412237555167]
  I-Design is a personalized interior designer that allows users to generate and visualize their design goals through natural language communication. I-Design starts with a team of large language model agents that engage in dialogues and logical reasoning with one another. The final design is then constructed in 3D by retrieving and integrating assets from an existing object database.
  arXiv  Detail & Related papers  (2024-04-03T16:17:53Z)
• Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints [53.66698106829144]
  We propose a unified model to handle a broad range of layout generation tasks. The model is based on continuous diffusion models. Experiment results show that LACE produces high-quality layouts.
  arXiv  Detail & Related papers  (2024-02-07T11:12:41Z)
• iBARLE: imBalance-Aware Room Layout Estimation [54.819085005591894]
  Room layout estimation predicts layouts from a single panorama. There are significant imbalances in real-world datasets including the dimensions of layout complexity, camera locations, and variation in scene appearance. We propose imBalance-Aware Room Layout Estimation (iBARLE) framework to address these issues. iBARLE consists of (1) Appearance Variation Generation (AVG) module, (2) Complex Structure Mix-up (CSMix) module, which enhances generalizability w.r.t. room structure, and (3) a gradient-based layout objective function.
  arXiv  Detail & Related papers  (2023-08-29T06:20:36Z)
• ATISS: Autoregressive Transformers for Indoor Scene Synthesis [112.63708524926689]
  We present ATISS, a novel autoregressive transformer architecture for creating synthetic indoor environments. We argue that this formulation is more natural, as it makes ATISS generally useful beyond fully automatic room layout synthesis. Our model is trained end-to-end as an autoregressive generative model using only labeled 3D bounding boxes as supervision.
  arXiv  Detail & Related papers  (2021-10-07T17:58:05Z)
• Multi-Agent Reinforcement Learning of 3D Furniture Layout Simulation in Indoor Graphics Scenes [3.4447129363520332]
  We explore the interior graphics scenes design task as a Markov decision process (MDP) in 3D simulation. The goal is to produce furniture layout in the 3D simulation of the indoor graphics scenes. We conduct experiments on a large-scale real-world interior layout dataset.
  arXiv  Detail & Related papers  (2021-02-18T03:20:35Z)
• Deep Reinforcement Learning for Producing Furniture Layout in Indoor Scenes [3.4447129363520332]
  In the industrial interior design process, professional designers plan the size and position of furniture in a room to achieve a satisfactory design for selling. We explore the interior scene design task as a Markov decision process (MDP), which is solved by deep reinforcement learning. Our numerical results demonstrate that the proposed model yields higher-quality layouts as compared with the state-of-art model.
  arXiv  Detail & Related papers  (2021-01-19T04:38:58Z)
• Deep Layout of Custom-size Furniture through Multiple-domain Learning [6.259404056725123]
  The proposed model combines a deep layout module, a domain attention module, a dimensional domain transfer module, and a custom-size module in the end-end training. We conduct experiments on a real-world interior layout dataset that contains $710,700$ designs from professional designers.
  arXiv  Detail & Related papers  (2020-12-15T07:32:13Z)
• Structural Plan of Indoor Scenes with Personalized Preferences [15.025764749987486]
  The proposed model is able to automatically produce the layout of objects of a particular indoor scene according to property owners' preferences. We provide an interior layout dataset that contains real-world 11000 designs from professional designers.
  arXiv  Detail & Related papers  (2020-08-04T04:46:19Z)
• Adversarial Model for Rotated Indoor Scenes Planning [15.025764749987486]
  We propose an adversarial model for producing furniture layout for interior scene when the interior room is rotated. The proposed model combines a conditional adversarial network, a rotation module, a mode module, and a rotation discriminator module. Our numerical results demonstrate that the proposed model yields higher-quality layouts for four types of rooms, including the bedroom, the bathroom, the study room, and the tatami room.
  arXiv  Detail & Related papers  (2020-06-24T07:29:07Z)
• Spatial Priming for Detecting Human-Object Interactions [89.22921959224396]
  We present a method for exploiting spatial layout information for detecting human-object interactions (HOIs) in images. The proposed method consists of a layout module which primes a visual module to predict the type of interaction between a human and an object. The proposed model reaches an mAP of 24.79% for HICO-Det dataset which is about 2.8% absolute points higher than the current state-of-the-art.
  arXiv  Detail & Related papers  (2020-04-09T23:20:30Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.