Inverse Tone Mapping On Msu Hdr Video
Metrics
HDR-PSNR
HDR-SSIM
HDR-VQM
Results
Performance results of various models on this benchmark
Model Name | HDR-PSNR | HDR-SSIM | HDR-VQM | Paper Title | Repository |
|---|---|---|---|---|---|
| HDRCNN | 33.0200 | 0.9663 | 0.1919 | HDR image reconstruction from a single exposure using deep CNNs | |
| KUNet | 32.5082 | 0.9864 | 0.2126 | KUNet: Imaging Knowledge-Inspired Single HDR Image Reconstruction | |
| HDRTVDN | 35.7459 | 0.9927 | 0.1138 | Learning a Practical SDR-to-HDRTV Up-conversion using New Dataset and Degradation Models | |
| ExpNet | 34.0555 | 0.9892 | 0.1942 | ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content | |
| HDRTVNet | 35.9721 | 0.9918 | 0.1296 | A New Journey from SDRTV to HDRTV | |
| twostageHDR | 31.6717 | 0.9884 | 0.1350 | A Two-stage Deep Network for High Dynamic Range Image Reconstruction | |
| SingleHDR | 34.2872 | 0.9845 | 0.2630 | Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline | |
| DeepHDR | 33.5267 | 0.9907 | 0.1000 | Single Image HDR Reconstruction Using a CNN with Masked Features and Perceptual Loss | - |
| HDRUNet | 34.9894 | 0.9845 | 0.1830 | HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization |
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