{"id":13444358,"url":"https://github.com/vinthony/awesome-deep-hdr","last_synced_at":"2026-01-25T09:34:41.355Z","repository":{"id":44463350,"uuid":"187169778","full_name":"vinthony/awesome-deep-hdr","owner":"vinthony","description":"A collection of deep learning based methods for HDR image 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Image Synthesis\n*  **_Deep high dynamic range imaging of dynamic scenes._** \u003cbr\u003e\n`SIGGRAPH Asia 2017` | [`Paper`](https://cseweb.ucsd.edu/~viscomp/projects/SIG17HDR/PaperData/SIGGRAPH17_HDR.pdf) | [`Project`](http://viscomp.ucsd.edu/projects/SIG17HDR/) | [`Code::matlab (Official)`](https://cseweb.ucsd.edu/~viscomp/projects/SIG17HDR/PaperData/SIGGRAPH17_HDR_Code_v1.0.zip) | [`Code::TensorFlow`](https://github.com/TH3CHARLie/deep-high-dynamic-range)\u003cbr\u003e\n\n* **_Multi-scale Dense Networks for Deep High Dynamic Range Imaging_** \u003cbr\u003e\n`WACV 2019`  | [`Paper`](https://ieeexplore.ieee.org/document/8658831)\n\n* **_Deep High Dynamic Range Imaging with Large Foreground Motions_**  \u003cbr\u003e\n`ECCV 2018` | [`paper`](https://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Shangzhe_Wu_Deep_High_Dynamic_ECCV_2018_paper.pdf) | [`project \u0026 code`](https://elliottwu.com/projects/hdr/)\n\n* **_Attention-guided Network for Ghost-free High Dynamic Range Imaging_** \u003cbr\u003e \n`CVPR 2019` | [`paper`](https://arxiv.org/abs/1904.10293) | [`code`](https://github.com/qingsenyangit/AHDRNet) | [`Project`](https://donggong1.github.io/ahdr.html)\n\n* **_Deep HDR Imaging via A Non-Local Network_** \u003cbr\u003e\n`TIP 2020` | [`paper`](https://ieeexplore.ieee.org/abstract/document/8989959) | [`code`](https://github.com/tuvovan/NHDRRNet)\n\n* **_HDR-GAN: HDR Image Reconstruction from Multi-Exposed LDR Images with Large Motions_** \u003cbr\u003e\n`TIP 2021` | [`paper`](https://arxiv.org/abs/2007.01628)\n\n### Single Image HDR Reconstruction\n\n* **_HDR image reconstruction from a single exposure using deep CNNs_** \u003cbr\u003e\n`SiGGRAPH Asia 2017` | [`Paper`](https://arxiv.org/abs/1710.07480) | [`Project`](http://hdrv.org/hdrcnn/)\n\n* **_ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content_** \u003cbr\u003e\n`Eurographics 2018/Computer Graphics Forum` | [`paper`](https://arxiv.org/pdf/1803.02266.pdf) | [`code`](https://github.com/dmarnerides/hdr-expandnet)\n\n* **_Deep Chain HDRI: Reconstructing a High Dynamic Range Image from a Single Low Dynamic Range Image_** \u003cbr\u003e\n`IEEE Access 2018` | [`Paper`](https://arxiv.org/abs/1801.06277) | [`Project`](https://siyeong-lee.github.io/hdr_vds_dataset/) | [`Dataset`](https://drive.google.com/drive/folders/1i7iTC6t6e_ZhyCq178V3-nN-IS5-5WOe)\n\n* **_Deep Recursive HDRI: Inverse Tone Mapping using Generative Adversarial Networks_**\u003cbr\u003e\n`ECCV 2018` | [`Paper`](http://openaccess.thecvf.com/content_ECCV_2018/papers/Siyeong_Lee_Deep_Recursive_HDRI_ECCV_2018_paper.pdf) |  [`code`](https://github.com/Siyeong-Lee/Deep_Recursive_HDRI)\n\n* **_Deep Reverse Tone Mapping_**  \u003cbr\u003e\n`SIGGRAPH ASIA 2017` | [`Paper`](http://www.npal.cs.tsukuba.ac.jp/~endo/projects/DrTMO/paper/DrTMO_SIGGRAPHAsia.pdf) | [`project \u0026 code`](http://www.npal.cs.tsukuba.ac.jp/~endo/projects/DrTMO/)\n\n* **_Hybrid Loss for Learning Single-Image-based HDR Reconstruction_** \u003cbr\u003e\n`ArXiv 2018` | [`Paper`](https://arxiv.org/abs/1812.07134)\n\n* **_FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network_** \u003cbr\u003e \n`Global SIP 2019` | [`Paper`](https://arxiv.org/abs/1912.11463) | [`Code`](https://github.com/mukulkhanna/fhdr)\n\n* **_Single Image HDR Reconstruction Using a CNN with Masked Features and Perceptual Loss_**  \u003cbr\u003e\n`SIGGRAPH 2020` | [`Paper`](https://arxiv.org/abs/2005.07335) | [`Code`](https://github.com/marcelsan/Deep-HdrReconstruction)\n\n*  **_Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline_** \u003cbr\u003e\n`CVPR 2020` | [`Paper`](https://arxiv.org/abs/2004.01179) | [`Code`](https://github.com/alex04072000/SingleHDR)\n\n* **_End-to-End Differentiable Learning to HDR Image Synthesis for Multi-exposure Images_** \u003cbr\u003e\n`AAAI 2021` | [`Paper`](https://arxiv.org/pdf/2006.15833.pdf)\n\n* **_Beyond Visual Attractiveness: Physically Plausible Single Image HDR Reconstruction for Spherical Panoramas_** \u003cbr\u003e\n`ArXiv 2021` | [`Paper`](https://arxiv.org/pdf/2103.12926.pdf)\n\n\n### HDR Video\n* **_Deep HDR Video from Sequences with Alternating Exposures_** \u003cbr\u003e\n`Eurographics 2019` | [`Paper`](https://people.engr.tamu.edu/nimak/Data/Eurographics19_HDRVideo.pdf)\n\n* **_Single-frame Regularization for Temporally Stable CNNs_** \u003cbr\u003e\n`CVPR 2019` | [`project`](http://hdrv.org/hdrcnn/cvpr2019)\n\n* **_Deep SR-ITM: Joint Learning of Super-Resolution and Inverse Tone-Mapping for 4K UHD HDR Applications_** \u003cbr\u003e \n`ICCV 2019`| [`paper`](https://arxiv.org/abs/1904.11176)\n\n* **_JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR Video_** \u003cbr\u003e \n`AAAI 2020`| [`paper`](https://arxiv.org/abs/1909.04391)\n\n\n\n* **_HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset_** \u003cbr\u003e\n `ICCV 2021` | [`ArXiv`](https://arxiv.org/pdf/2103.14943.pdf) | [`Project`](https://guanyingc.github.io/DeepHDRVideo/) | [`Code::Pytorch`](https://github.com/guanyingc/DeepHDRVideo) | [`Dataset`](https://github.com/guanyingc/DeepHDRVideo-Dataset)\n\n* **_A New Journey from SDRTV to HDRTV_** \u003cbr\u003e\n `ICCV 2021` | [`code`](https://github.com/chxy95/HDRTVNet)\n \n### Dataset\n* [[Kalantari Dataset in SIGGRAPH17]](https://cseweb.ucsd.edu/~viscomp/projects/SIG17HDR/)\n* [[CVPR19 Single Frame]](https://alex04072000.github.io/SingleHDR/)\n* [[NTIRE 2021 High Dynamic Range Challenge (Track 1 Single Frame)]](https://competitions.codalab.org/competitions/28161#participate-get-data)\n* [[NTIRE 2021 High Dynamic Range Challenge (Track 2 Multi Frame)]](https://competitions.codalab.org/competitions/28162)\n\u003e updating\n\n\n### Related\n\n* **_Deep Bilateral Learning for Real-Time Image Enhancement_** \u003cbr\u003e \n`SIGGRAPH 2017`| [`project`](https://groups.csail.mit.edu/graphics/hdrnet/)\n\n* **_Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time_** \u003cbr\u003e\n`TPAMI 2020` | [`Paper`](https://arxiv.org/abs/2009.14468) | [`Code`](https://github.com/HuiZeng/Image-Adaptive-3DLUT)\n\n* _HDR MATLAB/Octave Toolbox_ \u003cbr\u003e\n[[Github]](https://github.com/banterle/HDR_Toolbox)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvinthony%2Fawesome-deep-hdr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvinthony%2Fawesome-deep-hdr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvinthony%2Fawesome-deep-hdr/lists"}