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We propose a novel inverse rendering method that enables the transformation of existing indoor panoramas with new indoor furniture layouts under natural illumination. To achieve this, we captured indoor HDR panoramas along with real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Guanzhou Ji , Azadeh O. Sawyer , Srinivasa G. Narasimhan

We present a method to edit complex indoor lighting from a single image with its predicted depth and light source segmentation masks. This is an extremely challenging problem that requires modeling complex light transport, and disentangling…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Zhengqin Li , Jia Shi , Sai Bi , Rui Zhu , Kalyan Sunkavalli , Miloš Hašan , Zexiang Xu , Ravi Ramamoorthi , Manmohan Chandraker

A 3D digital scene contains many components: lights, materials and geometries, interacting to reach the desired appearance. Staging such a scene is time-consuming and requires both artistic and technical skills. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-07-10 Kai Yan , Fujun Luan , MiloŠ HaŠAn , Thibault Groueix , Valentin Deschaintre , Shuang Zhao

Recent single-view 3D generative methods have made significant advancements by leveraging knowledge distilled from extensive 3D object datasets. However, challenges persist in the synthesis of 3D scenes from a single view, primarily due to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Guo Pu , Yiming Zhao , Zhouhui Lian

This paper introduces a novel image-based rendering technique for jointly estimating indoor lighting and thermal conditions from paired indoor-outdoor high dynamic range (HDR) panoramas. Our method uses the indoor panorama to estimate the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Guanzhou Ji , Sriram Narayanan , Azadeh Sawyer , Srinivasa Narasimhan

Because of the diversity in lighting environments, existing illumination estimation techniques have been designed explicitly on indoor or outdoor environments. Methods have focused specifically on capturing accurate energy (e.g., through…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Mohammad Reza Karimi Dastjerdi , Jonathan Eisenmann , Yannick Hold-Geoffroy , Jean-François Lalonde

We propose a pipeline that leverages Stable Diffusion to improve inpainting results in the context of defurnishing -- the removal of furniture items from indoor panorama images. Specifically, we illustrate how increased context,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Mira Slavcheva , Dave Gausebeck , Kevin Chen , David Buchhofer , Azwad Sabik , Chen Ma , Sachal Dhillon , Olaf Brandt , Alan Dolhasz

We propose an automatic method to infer high dynamic range illumination from a single, limited field-of-view, low dynamic range photograph of an indoor scene. In contrast to previous work that relies on specialized image capture, user…

Computer Vision and Pattern Recognition · Computer Science 2017-11-22 Marc-André Gardner , Kalyan Sunkavalli , Ersin Yumer , Xiaohui Shen , Emiliano Gambaretto , Christian Gagné , Jean-François Lalonde

Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) input image is challenging due to missing details in under-/over-exposed regions caused by quantization and saturation of camera sensors. In contrast to…

Image and Video Processing · Electrical Eng. & Systems 2020-04-03 Yu-Lun Liu , Wei-Sheng Lai , Yu-Sheng Chen , Yi-Lung Kao , Ming-Hsuan Yang , Yung-Yu Chuang , Jia-Bin Huang

Single image scene relighting aims to generate a realistic new version of an input image so that it appears to be illuminated by a new target light condition. Although existing works have explored this problem from various perspectives,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Yixiong Yang , Hassan Ahmed Sial , Ramon Baldrich , Maria Vanrell

Mixed Reality scene relighting, where virtual changes to lighting conditions realistically interact with physical objects, producing authentic illumination and shadows, can be used in a variety of applications. One such application in real…

Graphics · Computer Science 2025-08-22 Hanwen Zhao , John Akers , Baback Elmieh , Ira Kemelmacher-Shlizerman

The rising availability of commercial $360^\circ$ cameras that democratize indoor scanning, has increased the interest for novel applications, such as interior space re-design. Diminished Reality (DR) fulfills the requirement of such…

Computer Vision and Pattern Recognition · Computer Science 2021-06-02 V. Gkitsas , V. Sterzentsenko , N. Zioulis , G. Albanis , D. Zarpalas

We present a self-supervised approach to in-the-wild image relighting that enables fully controllable, physically based illumination editing. We achieve this by combining the physical accuracy of traditional rendering with the…

Graphics · Computer Science 2025-08-08 Chris Careaga , Yağız Aksoy

We present a new lighting estimation and editing framework to generate high-dynamic-range (HDR) indoor panorama lighting from a single limited field-of-view (LFOV) image captured by low-dynamic-range (LDR) cameras. Existing lighting…

Computer Vision and Pattern Recognition · Computer Science 2022-08-01 Guangcong Wang , Yinuo Yang , Chen Change Loy , Ziwei Liu

Estimating a scene's lighting is a very important task when compositing synthetic content within real environments, with applications in mixed reality and post-production. In this work we present a data-driven model that estimates an HDR…

Computer Vision and Pattern Recognition · Computer Science 2020-05-19 Vasileios Gkitsas , Nikolaos Zioulis , Federico Alvarez , Dimitrios Zarpalas , Petros Daras

HDR reconstruction is an important task in computer vision with many industrial needs. The traditional approaches merge multiple exposure shots to generate HDRs that correspond to the physical quantity of illuminance of the scene. However,…

Computer Vision and Pattern Recognition · Computer Science 2021-03-25 Wei Wei , Li Guan , Yue Liu , Hao Kang , Haoxiang Li , Ying Wu , Gang Hua

Image based modeling and laser scanning are two commonly used approaches in large-scale architectural scene reconstruction nowadays. In order to generate a complete scene reconstruction, an effective way is to completely cover the scene…

Computer Vision and Pattern Recognition · Computer Science 2019-09-19 Xiang Gao , Shuhan Shen , Lingjie Zhu , Tianxin Shi , Zhiheng Wang , Zhanyi Hu

The low dynamic range (LDR) of common cameras fails to capture the rich contrast in natural scenes, resulting in loss of color and details in saturated pixels. Reconstructing the high dynamic range (HDR) of luminance present in the scene…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Sebastian Dille , Chris Careaga , Yağız Aksoy

It is very challenging to reconstruct a high dynamic range (HDR) from a low dynamic range (LDR) image as an ill-posed problem. This paper proposes a luminance attentive network named LANet for HDR reconstruction from a single LDR image. Our…

Computer Vision and Pattern Recognition · Computer Science 2021-09-15 Hanning Yu , Wentao Liu , Chengjiang Long , Bo Dong , Qin Zou , Chunxia Xiao

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
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