List of participants of MSU HDR Video Reconstruction Benchmark 2022: HLG

Name CNN Open Source Image/Video restoration Implementation Added by
Maxon No Video MSU
HDRCNN Yes Yes Video**+Image link MSU
HDRTV Yes Yes Video link MSU
ExpNet Yes Yes Video**+Image link MSU
DeepHDR Yes Yes Image link MSU
SingleHDR Yes Yes Image link MSU
Akyuz No Yes Image link MSU
Huo No Yes Image link MSU
HuoPhys No Yes Image link MSU
Kuo No Yes Image link MSU
KovOliv No Yes Image link MSU
* 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.

HDRTV

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

This network is divided into two parts: linearization and restoration.

  • Linearization: custom architecture
  • Restoration: ResNet


10 May 2022
See Also
MSU Video Quality Measurement Tool: Picture types
VQMT 14.0 Online help: List of all picture types available in VQMT and their aliases
MSU HDR Video Reconstruction Benchmark
The most comprehensive comparison of HDR video reconstruction methods
MSU HDR Video Reconstruction Benchmark Methodology
Evaluation Methodology of MSU HDR Video Reconstruction Benchmark
MSU HDR Video Reconstruction Benchmark Dataset
MSU HDR Video Reconstruction Benchmark Dataset
MSU Super-Resolution for Video Compression Benchmark 2022
Learn about the best SR methods for compressed videos and choose the best model to use with your codec
MSU Super-Resolution for Video Compression Benchmark Participants
The list of participants of MSU Super-Resolution for Video Compression Benchmark
Site structure