Image Reconstruction
531 papers with code • 5 benchmarks • 7 datasets
Benchmarks
These leaderboards are used to track progress in Image Reconstruction
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Libraries
Use these libraries to find Image Reconstruction models and implementations
General-100
CED
SEN12MS-CR
SEN12MS-CR-TS
Most implemented papers
Adaptive Image Sampling using Deep Learning and its Application on X-Ray Fluorescence Image Reconstruction
usstdqq/deep-adaptive-sampling-mask
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We propose an XRF image inpainting approach to address the issue of long scanning time, thus speeding up the scanning process while still maintaining the possibility to reconstruct a high quality XRF image.
f-AnoGAN: Fast Unsupervised Anomaly Detection with Generative Adversarial Networks
tSchlegl/f-AnoGAN
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Medical Image Analysis 2019
While supervised learning yields good results if expert labeled training data is available, the visual variability, and thus the vocabulary of findings, we can detect and exploit, is limited to the annotated lesions.
Implicit Generation and Generalization in Energy-Based Models
Energy based models (EBMs) are appealing due to their generality and simplicity in likelihood modeling, but have been traditionally difficult to train.
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
denisyarats/pytorch_sac_ae
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A promising approach is to learn a latent representation together with the control policy.
Image2StyleGAN++: How to Edit the Embedded Images?
pacifinapacific/StyleGAN_LatentEditor
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CVPR 2020
We propose Image2StyleGAN++, a flexible image editing framework with many applications.
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based Penalties
In this paper, we propose a proximal splitting methodology with a non-convex penalty function based on the heavy-tailed Cauchy distribution.
Accelerated MRI with Un-trained Neural Networks
Convolutional Neural Networks (CNNs) are highly effective for image reconstruction problems.
XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challenge
zaccharieramzi/fastmri-reproducible-benchmark
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We present a new neural network, the XPDNet, for MRI reconstruction from periodically under-sampled multi-coil data.
On hallucinations in tomographic image reconstruction
uiuc-comp-imaging-sci/hallucinations-tomo-recon
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The behavior of different reconstruction methods under the proposed formalism is discussed with the help of the numerical studies.
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.
