SSIM
302 papers with code • 1 benchmarks • 4 datasets
Libraries
Use these libraries to find SSIM models and implementations
O-HAZE
I-HAZE
VIDIT
DRealSR
Most implemented papers
OpenDVC: An Open Source Implementation of the DVC Video Compression Method
At the time of writing this report, several learned video compression methods are superior to DVC, but currently none of them provides open source codes.
ReconResNet: Regularised Residual Learning for MR Image Reconstruction of Undersampled Cartesian and Radial Data
It has been shown that the proposed framework can successfully reconstruct even for an acceleration factor of 20 for Cartesian (0. 968$\pm$0. 005) and 17 for radially (0. 962$\pm$0. 012) sampled data.
Single Image Reflection Separation with Perceptual Losses
ceciliavision/perceptual-reflection-removal
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CVPR 2018
Our loss function includes two perceptual losses: a feature loss from a visual perception network, and an adversarial loss that encodes characteristics of images in the transmission layers.
Joint Autoregressive and Hierarchical Priors for Learned Image Compression
InterDigitalInc/CompressAI
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NeurIPS 2018
While it is well known that autoregressive models come with a significant computational penalty, we find that in terms of compression performance, autoregressive and hierarchical priors are complementary and, together, exploit the probabilistic structure in the latents better than all previous learned models.
BASNet: Boundary-Aware Salient Object Detection
In this paper, we propose a predict-refine architecture, BASNet, and a new hybrid loss for Boundary-Aware Salient object detection.
Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks
In contrast, we cast the problem of cloud removal as a conditional image synthesis challenge, and we propose a trainable spatiotemporal generator network (STGAN) to remove clouds.
Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modules
ZhengxueCheng/Learned-Image-Compression-with-GMM-and-Attention
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In this paper, we explore the remaining redundancy of recent learned compression algorithms.
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
RenYang-home/HLVC
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CVPR 2020
In our HLVC approach, the hierarchical quality benefits the coding efficiency, since the high quality information facilitates the compression and enhancement of low quality frames at encoder and decoder sides, respectively.
CompressAI: a PyTorch library and evaluation platform for end-to-end compression research
InterDigitalInc/CompressAI
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This paper presents CompressAI, a platform that provides custom operations, layers, models and tools to research, develop and evaluate end-to-end image and video compression codecs.
Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction
Accelerating MRI scans is one of the principal outstanding problems in the MRI research community.
