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Related papers: Invertible Tone Mapping with Selectable Styles

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Few tone mapping operators (TMOs) take color management into consideration, limiting compression to luminance values only. This may lead to changes in image chroma and hues which are typically managed with a post-processing step. However,…

Computer Vision and Pattern Recognition · Computer Science 2017-11-27 E. Sikudova , T. Pouli , A. Artusi , A. O. Akyuz , F. Banterle , Z. M. Mazlumoglu , E. Reinhard

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

High dynamic range (HDR) video reconstruction from sequences captured with alternating exposures is a very challenging problem. Existing methods often align low dynamic range (LDR) input sequence in the image space using optical flow, and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-24 Guanying Chen , Chaofeng Chen , Shi Guo , Zhetong Liang , Kwan-Yee K. Wong , Lei Zhang

Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) image, namely inverse tone mapping (ITM), is challenging due to the lack of information in over- and under-exposed regions. Current methods focus exclusively…

Image and Video Processing · Electrical Eng. & Systems 2022-04-12 Juan Borrego-Carazo , Mete Ozay , Frederik Laboyrie , Paul Wisbey

Reconstruction of high-quality HDR images is at the core of modern computational photography. Significant progress has been made with multi-frame HDR reconstruction methods, producing high-resolution, rich and accurate color reconstructions…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Richard Shaw , Sibi Catley-Chandar , Ales Leonardis , Eduardo Perez-Pellitero

This paper reviews the first challenge on high-dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2021. This manuscript focuses on the newly…

Computer Vision and Pattern Recognition · Computer Science 2021-06-04 Eduardo Pérez-Pellitero , Sibi Catley-Chandar , Aleš Leonardis , Radu Timofte

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang

In this lecture note, we describe high dynamic range (HDR) imaging systems; such systems are able to represent luminances of much larger brightness and, typically, also a larger range of colors than conventional standard dynamic range (SDR)…

Graphics · Computer Science 2017-12-01 Alessandro Artusi , Thomas Richter , Touradj Ebrahimi , Rafal K. Mantiuk

This paper proposes the first non-flow-based deep framework for high dynamic range (HDR) imaging of dynamic scenes with large-scale foreground motions. In state-of-the-art deep HDR imaging, input images are first aligned using optical flows…

Computer Vision and Pattern Recognition · Computer Science 2018-07-25 Shangzhe Wu , Jiarui Xu , Yu-Wing Tai , Chi-Keung Tang

Image deep features extracted by pre-trained networks are known to contain rich and informative representations. In this paper, we present Deep Degradation Response (DDR), a method to quantify changes in image deep features under varying…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Juncheng Wu , Zhangkai Ni , Hanli Wang , Wenhan Yang , Yuyin Zhou , Shiqi Wang

Regular cameras and cell phones are able to capture limited luminosity. Thus, in terms of quality, most of the produced images from such devices are not similar to the real world. They are overly dark or too bright, and the details are not…

Computer Vision and Pattern Recognition · Computer Science 2022-12-07 Ali Reza Omrani , Davide Moroni

Single LDR to HDR reconstruction remains challenging for over-exposed regions where traditional methods often fail due to complete information loss. We present a training-free approach that enhances existing indirect and direct HDR…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Yo-Tin Lin , Su-Kai Chen , Hou-Ning Hu , Yen-Yu Lin , Yu-Lun Liu

The rapid adoption of HDR-capable devices has created a pressing need to convert the 8-bit Standard Dynamic Range (SDR) content into perceptually and physically accurate 10-bit High Dynamic Range (HDR). Existing inverse tone-mapping (ITM)…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Shreshth Saini , Hakan Gedik , Neil Birkbeck , Yilin Wang , Balu Adsumilli , Alan C. Bovik

As an important and practical way to obtain high dynamic range (HDR) video, HDR video reconstruction from sequences with alternating exposures is still less explored, mainly due to the lack of large-scale real-world datasets. Existing…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Yong Shu , Liquan Shen , Xiangyu Hu , Mengyao Li , Zihao Zhou

High Dynamic Range (HDR) generation remains challenging for generative models, which are largely limited to low dynamic range outputs. Recent diffusionbased approaches approximate HDR by generating multiple exposure-conditioned samples,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Pedram Fekri , WenChen Li , William Chen , Peter Altamirano

Coherent diffractive imaging is a technique that recovers the sample image by numerically inverting its diffraction pattern. We propose a generalization of this method for the inversion of multi-wavelength data. Using this approach, we show…

Optics · Physics 2020-05-08 Erik Malm , Edwin Fohtung , Anders Mikkelsen

This paper tackles high-dynamic-range (HDR) image reconstruction given only a single low-dynamic-range (LDR) image as input. While the existing methods focus on minimizing the mean-squared-error (MSE) between the target and reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2018-12-19 Kenta Moriwaki , Ryota Yoshihashi , Rei Kawakami , Shaodi You , Takeshi Naemura

Recent innovations shows that blending of details captured by single Low Dynamic Range (LDR) sensor overcomes the limitations of standard digital cameras to capture details from high dynamic range scene. We present a method to produce…

Computer Vision and Pattern Recognition · Computer Science 2022-07-12 Harbinder Singh , Dinesh Arora , Vinay Kumar

High-Dynamic-Range Wide-Color-Gamut (HDR-WCG) technology is becoming increasingly widespread, driving a growing need for converting Standard Dynamic Range (SDR) content to HDR. Existing methods primarily rely on fixed tone mapping…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Li Xu , Siqi Wang , Kepeng Xu , Gang He , Lin Zhang , Weiran Wang , Yu-Wing Tai

High dynamic range imaging (HDRI) for real-world dynamic scenes is challenging because moving objects may lead to hybrid degradation of low dynamic range and motion blur. Existing event-based approaches only focus on a separate task, while…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Li Xiaopeng , Zeng Zhaoyuan , Fan Cien , Zhao Chen , Deng Lei , Yu Lei
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