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Related papers: PanoRoom: From the Sphere to the 3D Layout

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Panorama images have a much larger field-of-view thus naturally encode enriched scene context information compared to standard perspective images, which however is not well exploited in the previous scene understanding methods. In this…

Computer Vision and Pattern Recognition · Computer Science 2021-08-25 Cheng Zhang , Zhaopeng Cui , Cai Chen , Shuaicheng Liu , Bing Zeng , Hujun Bao , Yinda 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

Panoramic image enables deeper understanding and more holistic perception of $360^\circ$ surrounding environment, which can naturally encode enriched scene context information compared to standard perspective image. Previous work has made…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Yuan Dong , Chuan Fang , Liefeng Bo , Zilong Dong , Ping Tan

One major goal of vision is to infer physical models of objects, surfaces, and their layout from sensors. In this paper, we aim to interpret indoor scenes from one RGBD image. Our representation encodes the layout of walls, which must…

Computer Vision and Pattern Recognition · Computer Science 2017-08-21 Ruiqi Guo , Chuhang Zou , Derek Hoiem

The goal of this paper is to take a single 2D image of a scene and recover the 3D structure in terms of a small set of factors: a layout representing the enclosing surfaces as well as a set of objects represented in terms of shape and pose.…

Computer Vision and Pattern Recognition · Computer Science 2018-04-25 Shubham Tulsiani , Saurabh Gupta , David Fouhey , Alexei A. Efros , Jitendra Malik

One major goal of vision is to infer physical models of objects, surfaces, and their layout from sensors. In this paper, we aim to interpret indoor scenes from one RGBD image. Our representation encodes the layout of orthogonal walls and…

Computer Vision and Pattern Recognition · Computer Science 2018-11-15 Chuhang Zou , Ruiqi Guo , Zhizhong Li , Derek Hoiem

We introduce the task of predicting functional 3D scene graphs for real-world indoor environments from posed RGB-D images. Unlike traditional 3D scene graphs that focus on spatial relationships of objects, functional 3D scene graphs capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Chenyangguang Zhang , Alexandros Delitzas , Fangjinhua Wang , Ruida Zhang , Xiangyang Ji , Marc Pollefeys , Francis Engelmann

The paper introduces an accurate solution to dense orthographic Non-Rigid Structure from Motion (NRSfM) in scenarios with severe occlusions or, likewise, inaccurate correspondences. We integrate a shape prior term into variational…

Computer Vision and Pattern Recognition · Computer Science 2017-12-21 Vladislav Golyanik , Torben Fetzer , Didier Stricker

Recovering structure and motion parameters given a image pair or a sequence of images is a well studied problem in computer vision. This is often achieved by employing Structure from Motion (SfM) or Simultaneous Localization and Mapping…

Computer Vision and Pattern Recognition · Computer Science 2018-11-07 Thanuja Dharmasiri , Andrew Spek , Tom Drummond

Given a single RGB panorama, the goal of 3D layout reconstruction is to estimate the room layout by predicting the corners, floor boundary, and ceiling boundary. A common approach has been to use standard convolutional networks to predict…

Computer Vision and Pattern Recognition · Computer Science 2021-04-20 Shivansh Rao , Vikas Kumar , Daniel Kifer , Lee Giles , Ankur Mali

We propose a novel framework for creating large-scale photorealistic datasets of indoor scenes, with ground truth geometry, material, lighting and semantics. Our goal is to make the dataset creation process widely accessible, transforming…

Most indoor 3D scene reconstruction methods focus on recovering 3D geometry and scene layout. In this work, we go beyond this to propose PhotoScene, a framework that takes input image(s) of a scene along with approximately aligned CAD…

Computer Vision and Pattern Recognition · Computer Science 2022-07-05 Yu-Ying Yeh , Zhengqin Li , Yannick Hold-Geoffroy , Rui Zhu , Zexiang Xu , Miloš Hašan , Kalyan Sunkavalli , Manmohan Chandraker

In this paper, we present PanoDreamer, a novel method for producing a coherent 360{\deg} 3D scene from a single input image. Unlike existing methods that generate the scene sequentially, we frame the problem as single-image panorama and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Avinash Paliwal , Xilong Zhou , Andrii Tsarov , Nima Khademi Kalantari

We tackle the problem of automatically reconstructing a complete 3D model of a scene from a single RGB image. This challenging task requires inferring the shape of both visible and occluded surfaces. Our approach utilizes viewer-centered,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-28 Daeyun Shin , Zhile Ren , Erik B. Sudderth , Charless C. Fowlkes

Modern scene reconstruction methods are able to accurately recover 3D surfaces that are visible in one or more images. However, this leads to incomplete reconstructions, missing all occluded surfaces. While much progress has been made on…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Sam Bahrami , Dylan Campbell

Reconstructing geometry and topology structures from raw unstructured data has always been an important research topic in indoor mapping research. In this paper, we aim to reconstruct the floorplan with a vectorized representation from…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Yuzhou Liu , Lingjie Zhu , Xiaodong Ma , Hanqiao Ye , Xiang Gao , Xianwei Zheng , Shuhan Shen

We propose a novel framework for comprehensive indoor 3D reconstruction using Gaussian representations, called OmniIndoor3D. This framework enables accurate appearance, geometry, and panoptic reconstruction of diverse indoor scenes captured…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Xiaobao Wei , Xiaoan Zhang , Hao Wang , Qingpo Wuwu , Ming Lu , Wenzhao Zheng , Shanghang Zhang

The task of estimating the spatial layout of cluttered indoor scenes from a single RGB image is addressed in this work. Existing solutions to this problems largely rely on hand-craft features and vanishing lines, and they often fail in…

Computer Vision and Pattern Recognition · Computer Science 2016-07-05 Yuzhuo Ren , Chen Chen , Shangwen Li , C. -C. Jay Kuo

We propose an algorithm to predict room layout from a single image that generalizes across panoramas and perspective images, cuboid layouts and more general layouts (e.g. L-shape room). Our method operates directly on the panoramic image,…

Computer Vision and Pattern Recognition · Computer Science 2018-03-28 Chuhang Zou , Alex Colburn , Qi Shan , Derek Hoiem

In this paper, we address the inverse problem of reconstructing a scene as well as the camera motion from the image sequence taken by an omni-directional camera. Our structure from motion results give sharp conditions under which the…

Computer Vision and Pattern Recognition · Computer Science 2007-08-21 Oliver Knill , Jose Ramirez-Herran
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