On the public citation graph

Ecall: Expectation-Calibrated Learning for Unsupervised Blind Deconvolution

https://doi.org/10.2139/ssrn.5003900
0 signed · 40 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-0-387-69277-7openalex-snapshot
Variational Methods in Imaging
inferredcites →https://doi.org/10.1007/978-1-4757-3264-1openalex-snapshot
The Nature of Statistical Learning Theory
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46487-9_14openalex-snapshot
A Neural Approach to Blind Motion Deblurring
inferredcites →https://doi.org/10.1007/978-3-319-66709-6_6openalex-snapshot
Motion Deblurring in the Wild
inferredcites →https://doi.org/10.1007/978-3-642-15549-9_12openalex-snapshot
Two-Phase Kernel Estimation for Robust Motion Deblurring
inferredcites →https://doi.org/10.1007/978-3-642-33783-3_25openalex-snapshot
Bayesian Blind Deconvolution with General Sparse Image Priors
inferredcites →https://doi.org/10.1016/0167-2789(92)90242-fopenalex-snapshot
Nonlinear total variation based noise removal algorithms
inferredcites →https://doi.org/10.1088/1361-6420/aaa4a7openalex-snapshot
Convex blind image deconvolution with inverse filtering
inferredcites →https://doi.org/10.1088/1361-6420/aba415openalex-snapshot
Computed tomography reconstruction using deep image prior and learned reconstruction methods
inferredcites →https://doi.org/10.1088/1361-6420/ac4edeopenalex-snapshot
Un-supervised learning for blind image deconvolution via Monte-Carlo sampling
inferredcites →https://doi.org/10.1109/79.489268openalex-snapshot
Blind image deconvolution
inferredcites →https://doi.org/10.1109/83.661187openalex-snapshot
Total variation blind deconvolution
inferredcites →https://doi.org/10.1109/cvpr.2011.5995308openalex-snapshot
Efficient marginal likelihood optimization in blind deconvolution
inferredcites →https://doi.org/10.1109/cvpr.2011.5995521openalex-snapshot
Blind deconvolution using a normalized sparsity measure
inferredcites →https://doi.org/10.1109/cvpr.2013.147openalex-snapshot
Unnatural L0 Sparse Representation for Natural Image Deblurring
inferredcites →https://doi.org/10.1109/cvpr.2015.7298677openalex-snapshot
Learning a convolutional neural network for non-uniform motion blur removal
inferredcites →https://doi.org/10.1109/cvpr.2016.180openalex-snapshot
Blind Image Deblurring Using Dark Channel Prior
inferredcites →https://doi.org/10.1109/cvpr.2016.202openalex-snapshot
Blind Image Deconvolution by Automatic Gradient Activation
inferredcites →https://doi.org/10.1109/cvpr.2017.35openalex-snapshot
Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring
inferredcites →https://doi.org/10.1109/cvpr.2017.405openalex-snapshot
From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur
inferredcites →https://doi.org/10.1109/cvpr.2018.00267openalex-snapshot
Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00853openalex-snapshot
Scale-Recurrent Network for Deep Image Deblurring
inferredcites →https://doi.org/10.1109/cvpr.2018.00854openalex-snapshot
DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
inferredcites →https://doi.org/10.1109/cvpr.2019.01047openalex-snapshot
Unsupervised Domain-Specific Deblurring via Disentangled Representations
inferredcites →https://doi.org/10.1109/cvpr.2019.01128openalex-snapshot
“Double-DIP”: Unsupervised Image Decomposition via Coupled Deep-Image-Priors
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00340openalex-snapshot
Neural Blind Deconvolution Using Deep Priors
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00821openalex-snapshot
StarGAN v2: Diverse Image Synthesis for Multiple Domains
inferredcites →https://doi.org/10.1109/cvprw.2009.5206815openalex-snapshot
Understanding and evaluating blind deconvolution algorithms
inferredcites →https://doi.org/10.1109/iccv.2017.244openalex-snapshot
Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
inferredcites →https://doi.org/10.1109/iccvw.2017.353openalex-snapshot
Deep Generative Filter for Motion Deblurring
inferredcites →https://doi.org/10.1109/icip.2008.4711802openalex-snapshot
Reducing boundary artifacts in image deconvolution
inferredcites →https://doi.org/10.1109/msp.2017.2765202openalex-snapshot
Generative Adversarial Networks: An Overview
inferredcites →https://doi.org/10.1109/tpami.2015.2481418openalex-snapshot
Learning to Deblur
inferredcites →https://doi.org/10.1137/080724289openalex-snapshot
Nonlinear Inverse Scale Space Methods for Total Variation Blind Deconvolution
inferredcites →https://doi.org/10.1145/1141911.1141956openalex-snapshot
Removing camera shake from a single photograph
inferredcites →https://doi.org/10.1145/1360612.1360672openalex-snapshot
High-quality motion deblurring from a single image
inferredcites →https://doi.org/10.1145/1661412.1618491openalex-snapshot
Fast motion deblurring
inferredcites →https://doi.org/10.48550/arxiv.1305.2362openalex-snapshot
Revisiting Bayesian Blind Deconvolution
inferredcites →https://doi.org/10.48550/arxiv.1711.05101openalex-snapshot
Decoupled Weight Decay Regularization
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.