SSIM
396 papers with code • 1 benchmarks • 4 datasets
Libraries
Use these libraries to find SSIM models and implementations
I-HAZE
DRealSR
DocUNet
VIDIT
Most implemented papers
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
richzhang/PerceptualSimilarity
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CVPR 2018
We systematically evaluate deep features across different architectures and tasks and compare them with classic metrics.
Variational image compression with a scale hyperprior
InterDigitalInc/CompressAI
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ICLR 2018
We describe an end-to-end trainable model for image compression based on variational autoencoders.
End-to-end Optimized Image Compression
We describe an image compression method, consisting of a nonlinear analysis transformation, a uniform quantizer, and a nonlinear synthesis transformation.
Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
Booooooooooo/CSD
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Convolutional neural networks (CNNs) are highly successful for super-resolution (SR) but often require sophisticated architectures with heavy memory cost and computational overhead, significantly restricts their practical deployments on resource-limited devices.
A Fully Progressive Approach to Single-Image Super-Resolution
fperazzi/proSR
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Recent deep learning approaches to single image super-resolution have achieved impressive results in terms of traditional error measures and perceptual quality.
TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network
In this work, we present the Text Conditioned Auxiliary Classifier Generative Adversarial Network, (TAC-GAN) a text to image Generative Adversarial Network (GAN) for synthesizing images from their text descriptions.
Learned Primal-dual Reconstruction
We propose the Learned Primal-Dual algorithm for tomographic reconstruction.
End-to-end Trained CNN Encode-Decoder Networks for Image Steganography
All the existing image steganography methods use manually crafted features to hide binary payloads into cover images.
DVC: An End-to-end Deep Video Compression Framework
Conventional video compression approaches use the predictive coding architecture and encode the corresponding motion information and residual information.
Progressive Image Deraining Networks: A Better and Simpler Baseline
To handle this issue, this paper provides a better and simpler baseline deraining network by considering network architecture, input and output, and loss functions.
