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computer-vision-4

inverse tone mapping

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content

Thomas Bashford-rogers, Kurt Debattista, Demetris Marnerides, Jonathan Hatchett•Mon Mar 05 2018

This paper presents a method for generating HDR content from LDR content based on deep Convolutional Neural Networks (CNNs) termed ExpandNet, which accepts LDR images as input and generates images with an expanded range in an end‐to‐end fashion.

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Deep Recursive HDRI: Inverse Tone Mapping Using Generative Adversarial Networks

Siyeong Lee, Gwon Hwan An, Suk-ju Kang•Fri Sep 07 2018

The proposed method is the first framework to create high dynamic range images based on the estimated multi-exposure stack using the conditional generative adversarial network structure and is significantly similar to the ground truth than other state-of-the-art algorithms.

123 0

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Deep SR-ITM: Joint Learning of Super-Resolution and Inverse Tone-Mapping for 4K UHD HDR Applications

Jihyong Oh, Munchurl Kim, S. Kim•Wed Apr 24 2019

This paper proposes a joint super-resolution (SR) and inverse tone-mapping (ITM) framework, called Deep SR-ITM, which learns the direct mapping from LR SDR video to their HR HDR version, and shows good subjective quality with increased contrast and details, outperforming the previous joint SR and ITM method.

110 0

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Luminance Attentive Networks for HDR Image and Panorama Reconstruction

Chunxia Xiao, Chengjiang Long, Hanning Yu, Wentao Liu, Bo Dong, Qin Zou•Mon Sep 13 2021

Extensive experiments show that the proposed approach LANet can reconstruct visually convincing HDR images and demonstrate its superiority over state‐of‐the‐art approaches in terms of all metrics in inverse tone mapping.

36 0

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Unsupervised HDR Imaging: What Can Be Learned from a Single 8-bit Video?

Thomas Bashford-rogers, F. Banterle, Kurt Debattista, Demetris Marnerides•Thu Feb 10 2022

This work shows that, in many cases, a single SDR video is sufficient to be able to generate an HDR video of the same quality or better than other state-of-the-art methods.

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Joint Super-Resolution and Inverse Tone-Mapping: A Feature Decomposition Aggregation Network and A New Benchmark

Yuchen Yang, Liang Wang, Gang Xu, Jun Xu, Xiantong Zhen, Ming-Ming Cheng Nankai University, Institute of Automation, Cas, U. Amsterdam, Inception Institute of Artificial Intelligence•Wed Jul 06 2022

A lightweight Feature Decomposition Aggregation Network (FDAN) is proposed that is efficient and outperforms state-of-the-art methods on joint SR-ITM and develops a Hierarchical FeatureDecomposition Group by cascading FDBs for powerful multi-level feature decomposition.

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Distilling Style from Image Pairs for Global Forward and Inverse Tone Mapping

Rafał K. Mantiuk, Param Hanji, Aamir Mustafa•Thu Sep 29 2022

This work shows that information about the style can be distilled from collections of image pairs and encoded into a 2- or 3-dimensional vector, which gives not only an efficient representation but also an interpretable latent space for editing the image style.

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Lightweight improved residual network for efficient inverse tone mapping

Lei Zhang, Jun Xu, Xiantong Zhen, Liqi Xue, Tian-Ming Xu, Yong-ji Song, Yan Liu•Fri Jul 07 2023

A new Improved Residual Block (IRB) is proposed to extract and fuse multi-layer features for fine-grained HDR image reconstruction to enhance the power of popular residual block for efficient ITM.

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inverse tone mapping | State-of-the-Art