HDR Reconstruction
19 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in HDR Reconstruction
MSU HDR Video Reconstruction Benchmark
SI-HDR
Most implemented papers
HDR image reconstruction from a single exposure using deep CNNs
We demonstrate that our approach can reconstruct high-resolution visually convincing HDR results in a wide range of situations, and that it generalizes well to reconstruction of images captured with arbitrary and low-end cameras that use unknown camera response functions and post-processing.
Deep HDR Imaging via A Non-Local Network
tuvovan/NHDRRNet
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In NHDRRnet, we first adopt an Unet architecture to fuse all inputs and map the fusion results into a low-dimensional deep feature space.
Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline
alex04072000/SingleHDR
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CVPR 2020
We model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization.
HDR-GAN: HDR Image Reconstruction from Multi-Exposed LDR Images with Large Motions
nonu116/HDR-GAN
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To address these two problems, we propose in this paper a novel GAN-based model, HDR-GAN, for synthesizing HDR images from multi-exposed LDR images.
HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset
guanyingc/DeepHDRVideo
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ICCV 2021
Secondly, we conduct more sophisticated alignment and temporal fusion in the feature space of the coarse HDR video to produce better reconstruction.
HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization
chxy95/HDRUNet
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In this work, we propose a novel learning-based approach using a spatially dynamic encoder-decoder network, HDRUNet, to learn an end-to-end mapping for single image HDR reconstruction with denoising and dequantization.
NTIRE 2021 Challenge on High Dynamic Range Imaging: Dataset, Methods and Results
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.
How to cheat with metrics in single-image HDR reconstruction
Here, we reproduce a typical evaluation using existing as well as simulated SI-HDR methods to demonstrate how different aspects of the problem affect objective quality metrics.
Luminance Attentive Networks for HDR Image and Panorama Reconstruction
lwt3437/lanet
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Based on this observation, we propose a novel normalization method called " HDR calibration " for HDR images stored in relative luminance, calibrating HDR images into a similar luminance scale according to the LDR images.
Comparison of single image HDR reconstruction methods — the caveats of quality assessment
As the problem of reconstructing high dynamic range (HDR) images from a single exposure has attracted much research effort, it is essential to provide a robust protocol and clear guidelines on how to evaluate and compare new methods.
