A Survey of 3D Indoor Scene Synthesis

Zhang, Song Hai; Zhang, Shao Kui; Liang, Yuan; Hall, Peter M.

doi:10.1007/s11390-019-1929-5

Cited by 50 publications

(30 citation statements)

References 85 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the category of practical applications of 3D object arrangement, furniture arrangement is an important research topic in computer graphics. According to the recent furniture layout review, 9 the layout problem requires a lot of prior knowledge to select reasonable objects and arrange objects appropriately. The existing works on 3D object synthesis have mainly solved two subproblems.…”

Section: Object Arrangementmentioning

confidence: 99%

Bas‐relief layout arrangement via automatic method optimization

Mao

Zhang

et al. 2021

Computer Animation & Virtual

View full text Add to dashboard Cite

It is significant to achieve automatic arrangement for bas-relief layout which can be noticeably more efficient than the time-consuming manual process. In fact, nearly none work has been reported in terms of bas-relief layout arrangement. In this paper, we propose a novel approach to tackle this problem. Specifically, we first identify the evaluation indicators to account for different aesthetic factors, and model the goodness of each indicator. We then cast the bas-relief layout as a combinatorial optimization problem based on those evaluation indicators and a geometric mean model. The contribution of this paper is to propose an objective function for bas-relief layout and apply simulated annealing algorithm for optimization. Experiments show that our method is effective, in terms of layout arrangement for bas-relief generation. In addition, this method can synthesize a few models arrangement and investigate which evaluation indicators will affect the aesthetic perception of the bas-relief.

show abstract

Section: Object Arrangementmentioning

confidence: 99%

Bas‐relief layout arrangement via automatic method optimization

Mao

Zhang

et al. 2021

Computer Animation & Virtual

View full text Add to dashboard Cite

show abstract

“…Indoor scene synthesis aims to generate a feasible furniture layout of various object classes that satisfy both functional and aesthetic criteria [50]. Early work of synthetic generation focused on hard-coded rules, guidelines and grammar, following a procedural approach for this problem [4,45,11,30,48,46].…”

Section: Scene Synthesismentioning

confidence: 99%

Contextual Scene Augmentation and Synthesis via GSACNet

Keshavarzi¹,

Christian²,

Shrivastava³

et al. 2021

Preprint

View full text Add to dashboard Cite

Indoor scene augmentation has become an emerging topic in the field of computer vision and graphics with applications in augmented and virtual reality. However, current state-of-the-art systems using deep neural networks require large datasets for training. In this paper we introduce GSACNet, a contextual scene augmentation system that can be trained with limited scene priors. GSACNet utilizes a novel parametric data augmentation method combined with a Graph Attention and Siamese network architecture followed by an Autoencoder network to facilitate training with small datasets. We show the effectiveness of our proposed system by conducting ablation and comparative studies with alternative systems on the Matterport3D dataset. Our results indicate that our scene augmentation outperforms prior art in scene synthesis with limited scene priors available.

show abstract

“…We have found that the Social Placement Choice problem we investigate in this paper shares objectives with realistic indoor scene synthesis [14], in that it also tries to find implicit or explicit rules to help decide of socially acceptable object placement For example, in [15], Yu et al used a set of rules, automatically learned from human-designed indoor environments (e.g. distance/orientation to walls/specific objects, pathways between doors,.…”

Section: Related Workmentioning

confidence: 99%

Modeling a Social Placement Cost to Extend Navigation Among Movable Obstacles (NAMO) Algorithms

Renault

Saraydaryan

Simonin

2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

View full text Add to dashboard Cite

Current Navigation Among Movable Obstacles (NAMO) algorithms focus on finding a path for the robot that only optimizes the displacement cost of navigating and moving obstacles out of its way. However, in a human environment, this focus may lead the robot to leave the space in a socially inappropriate state that may hamper human activity (i.e. by blocking access to doors, corridors, rooms or objects of interest). In this paper, we tackle this problem of "Social Placement Choice" by building a social occupation costmap, built using only geometrical information. We present how existing NAMO algorithms can be extended by exploiting this new cost map. Then, we show the effectiveness of this approach with simulations, and provide additional evaluation criteria to assess the social acceptability of plans.

show abstract

A Survey of 3D Indoor Scene Synthesis

Cited by 50 publications

References 85 publications

Bas‐relief layout arrangement via automatic method optimization

Bas‐relief layout arrangement via automatic method optimization

Contextual Scene Augmentation and Synthesis via GSACNet

Modeling a Social Placement Cost to Extend Navigation Among Movable Obstacles (NAMO) Algorithms

Contact Info

Product

Resources

About