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Related papers: Fast 3D Indoor Scene Synthesis with Discrete and E…

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We present a structured graph variational autoencoder for generating the layout of indoor 3D scenes. Given the room type (e.g., living room or library) and the room layout (e.g., room elements such as floor and walls), our architecture…

Computer Vision and Pattern Recognition · Computer Science 2022-07-27 Aditya Chattopadhyay , Xi Zhang , David Paul Wipf , Himanshu Arora , Rene Vidal

Dense indoor scene modeling from 2D images has been bottlenecked due to the absence of depth information and cluttered occlusions. We present an automatic indoor scene modeling approach using deep features from neural networks. Given a…

Computer Vision and Pattern Recognition · Computer Science 2020-02-25 Yinyu Nie , Shihui Guo , Jian Chang , Xiaoguang Han , Jiahui Huang , Shi-Min Hu , Jian Jun Zhang

In this paper, we propose a novel procedure for 3D layout recovery of indoor scenes from single 360 degrees panoramic images. With such images, all scene is seen at once, allowing to recover closed geometries. Our method combines…

Computer Vision and Pattern Recognition · Computer Science 2018-06-22 Clara Fernandez-Labrador , Alejandro Perez-Yus , Gonzalo Lopez-Nicolas , Jose J. Guerrero

We present an approach to predict future video frames given a sequence of continuous video frames in the past. Instead of synthesizing images directly, our approach is designed to understand the complex scene dynamics by decoupling the…

Computer Vision and Pattern Recognition · Computer Science 2020-04-16 Yue Wu , Rongrong Gao , Jaesik Park , Qifeng Chen

Novel view synthesis of indoor scenes can be achieved by capturing a monocular video sequence of the environment. However, redundant information caused by artificial movements in the input video data reduces the efficiency of scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Zehao Wang , Han Zhou , Matthew B. Blaschko , Tinne Tuytelaars , Minye Wu

Synthesizing realistic 3D indoor scenes is a challenging task that traditionally relies on manual arrangement and annotation by expert designers. Recent advances in autoregressive models have automated this process, but they often lack…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Qi Sun , Hang Zhou , Wengang Zhou , Li Li , Houqiang Li

This paper presents an algorithm for indoor layout estimation and reconstruction through the fusion of a sequence of captured images and LiDAR data sets. In the proposed system, a movable platform collects both intensity images and 2D LiDAR…

Computer Vision and Pattern Recognition · Computer Science 2020-01-16 Jieyu Li , Robert L Stevenson

We introduce a novel method for dynamic free-view synthesis of an ambient scenes from a monocular capture bringing a immersive quality to the viewing experience. Our method builds upon the recent advancements in 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Meng-Li Shih , Jia-Bin Huang , Changil Kim , Rajvi Shah , Johannes Kopf , Chen Gao

The use of coarse-grained layouts for controllable synthesis of complex scene images via deep generative models has recently gained popularity. However, results of current approaches still fall short of their promise of high-resolution…

Computer Vision and Pattern Recognition · Computer Science 2021-05-14 Manuel Jahn , Robin Rombach , Björn Ommer

Controllable scene synthesis aims to create interactive environments for various industrial use cases. Scene graphs provide a highly suitable interface to facilitate these applications by abstracting the scene context in a compact manner.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Guangyao Zhai , Evin Pınar Örnek , Shun-Cheng Wu , Yan Di , Federico Tombari , Nassir Navab , Benjamin Busam

The remarkable achievements of both generative models of 2D images and neural field representations for 3D scenes present a compelling opportunity to integrate the strengths of both approaches. In this work, we propose a methodology that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Azmi Haider , Dan Rosenbaum

3D indoor scene generation is an important problem for the design of digital and real-world environments. To automate this process, a scene generation model should be able to not only generate plausible scene layouts, but also take into…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Kelly O. Marshall , Omid Poursaeed , Sergiu Oprea , Amit Kumar , Anushrut Jignasu , Chinmay Hegde , Yilei Li , Rakesh Ranjan

In this paper, we propose an assistive model that supports professional interior designers to produce industrial interior decoration solutions and to meet the personalized preferences of the property owners. The proposed model is able to…

Computer Vision and Pattern Recognition · Computer Science 2020-08-06 Xinhan Di , Pengqian Yu , Hong Zhu , Lei Cai , Qiuyan Sheng , Changyu Sun

Implicit neural representation has demonstrated promising results in 3D reconstruction on various scenes. However, existing approaches either struggle to model fast-moving objects or are incapable of handling large-scale camera ego-motions…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Tianchen Deng , Yanbo Wang , Yejia Liu , Chenpeng Su , Jingchuan Wang , Danwei Wang , Shao-Yuan Lo , Weidong Chen

Based on the Manhattan World assumption, most existing indoor layout estimation schemes focus on recovering layouts from vertically compressed 1D sequences. However, the compression procedure confuses the semantics of different planes,…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Zhijie Shen , Zishuo Zheng , Chunyu Lin , Lang Nie , Kang Liao , Shuai Zheng , Yao Zhao

High-fidelity 3D scene reconstruction has been substantially advanced by recent progress in neural fields. However, most existing methods train a separate network from scratch for each individual scene. This is not scalable, inefficient,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Yang Fu , Shalini De Mello , Xueting Li , Amey Kulkarni , Jan Kautz , Xiaolong Wang , Sifei Liu

Designing a 3D representation of a dynamic scene for fast optimization and rendering is a challenging task. While recent explicit representations enable fast learning and rendering of dynamic radiance fields, they require a dense set of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Nagabhushan Somraj , Kapil Choudhary , Sai Harsha Mupparaju , Rajiv Soundararajan

Robotic manipulation systems operating in complex environments rely on perception systems that provide information about the geometry (pose and 3D shape) of the objects in the scene along with other semantic information such as object…

Robotics · Computer Science 2023-05-17 Shubham Agrawal , Nikhil Chavan-Dafle , Isaac Kasahara , Selim Engin , Jinwook Huh , Volkan Isler

We present a method that simultaneously addresses the tasks of dynamic scene novel-view synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We follow an analysis-by-synthesis framework, inspired by recent work…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Jonathon Luiten , Georgios Kopanas , Bastian Leibe , Deva Ramanan

3D point cloud understanding has made great progress in recent years. However, one major bottleneck is the scarcity of annotated real datasets, especially compared to 2D object detection tasks, since a large amount of labor is involved in…

Computer Vision and Pattern Recognition · Computer Science 2021-08-18 Yongming Rao , Benlin Liu , Yi Wei , Jiwen Lu , Cho-Jui Hsieh , Jie Zhou