List of participants of MSU HDR Video Reconstruction Benchmark: HLG

Name Uses AI Open Source Image/Video restoration Implementation
Maxon No Video
HDRCNN Yes Yes Video*+Image link
HDRTVNet Yes Yes Video link
ExpNet Yes Yes Video*+Image link
DeepHDR Yes Yes Image link
SingleHDR Yes Yes Image link
Akyuz No Yes Image link
Huo No Yes Image link
HuoPhys No Yes Image link
Kuo No Yes Image link
KovOliv No Yes Image link
HDRUNet Yes Yes Image link
KUNet Yes Yes Image link
twostageHDR Yes Yes Image link

* Originally designed for image restoration, but has a video restoration option

Overview of neural network method architectures

HDRCNN

UNet-VGG-16 with skip connections neural network.

HDRTVNet

3 sequentially trained networks:

  • Custom architecture
  • ResNet
  • UNet based GAN

ExpandNet

  • Neural network with three parallel branches. They differ in the size of the convolution core
  • Concatenation followed by convolution processing

DeepHDR

UNet-VGG-like with skip connections neural network.

SingleHDR

Network which is divided into two parts: linearization and restoration.

  • Linearization: custom architecture
  • Restoration: ResNet


10 May 2022
See Also
MSU Image- and video-quality metrics analysis
Description of a project in MSU Graphics and Media Laboratory
Learning-Based Image Compression Benchmark
Super-Resolution Quality Metrics Benchmark
Discover 66 Super-Resolution Quality Metrics and choose the most appropriate for your videos
Video Saliency Prediction Benchmark
Explore the best video saliency prediction (VSP) algorithms
Super-Resolution for Video Compression Benchmark
Learn about the best SR methods for compressed videos and choose the best model to use with your codec
Metrics Robustness Benchmark
Check your image or video quality metric for robustness to adversarial attacks
Site structure