Paper Citation Record · LEDGER

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2511.10806.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2511.10806 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T22:24:22.920907Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation 8ec94ba3-7a03-45b5-aeb0-43b053b56f72 · outbound

This paper cites Mosaddek Khan.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Mosaddek Khan

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:17.577172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75149471-68c5-434f-8ef0-cfb0f63029d8 · outbound

This paper cites Estimating an image’s blur kernel using natural image statis- tics, and deblurring it: An analysis of the goldstein-fattal method.Image Processing On Line, 8:282–304, 2018.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Estimating an image’s blur kernel using natural image statis- tics, and deblurring it: An analysis of the goldstein-fattal method.Image Processing On Line, 8:282–304, 2018

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:17.723578Z

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Observation 931a832b-848d-4f08-8752-9bd9dd2d9b56 · outbound

This paper cites Simple baselines for image restoration.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Simple baselines for image restoration

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:17.793247Z

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Observation 351a8148-a473-425f-a60f-5548b2befec7 · outbound

This paper cites Image deblurring based on an improved cnn- transformer combination network.Applied Sciences, 13(1),.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Image deblurring based on an improved cnn- transformer combination network.Applied Sciences, 13(1),

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:17.960264Z

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Observation 23637d8f-a5b3-4c54-a7fa-78a9194687d2 · outbound

This paper cites Nbnet: Noise basis learning for image denoising with subspace projection.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Nbnet: Noise basis learning for image denoising with subspace projection

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:18.152333Z

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Unavailable: canonical work link unavailable.

Observation 26a0c703-b493-4196-b406-eb1b9eefc5bb · outbound

This paper cites Rethinking coarse-to-fine approach in single image deblurring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Rethinking coarse-to-fine approach in single image deblurring

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:18.348571Z

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Unavailable: canonical work link unavailable.

Observation 4f05a13e-5993-45c9-aba8-9bb741cb8075 · outbound

This paper cites Nafssr: Stereo image super-resolution using nafnet.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Nafssr: Stereo image super-resolution using nafnet

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:18.469073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08240adf-9fdc-4d68-857d-8b36263d82f1 · outbound

This paper cites Image deblurring by sparsity constraint on the fourier coefficients.Numerical Algorithms, 72, 2016.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Image deblurring by sparsity constraint on the fourier coefficients.Numerical Algorithms, 72, 2016

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:18.609090Z

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Observation 22fdaa84-6910-43f7-ab16-6852ae6586e9 · outbound

This paper cites Image super-resolution using deep convolutional net- works.IEEE transactions on pattern analysis and machine intelligence, 38(2):295–307, 2016.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Image super-resolution using deep convolutional net- works.IEEE transactions on pattern analysis and machine intelligence, 38(2):295–307, 2016

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:18.770669Z

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Unavailable: canonical work link unavailable.

Observation 86b96520-be63-4702-a25a-e2ee540aaba0 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:18.951078Z

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Unavailable: canonical work link unavailable.

Observation a4a56ba8-78b4-4510-8973-341d6846c0a7 · outbound

This paper cites Dy- namic scene deblurring with parameter selective sharing and nested skip connections.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Dy- namic scene deblurring with parameter selective sharing and nested skip connections

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:19.097077Z

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Unavailable: canonical work link unavailable.

Observation 71e93a57-e800-4d61-a3bc-bab588434b92 · outbound

This paper cites A survey on vision transformer.IEEE Transactions on Pattern Analysis and Machine Intelligence, PP:1–1, 2020.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring A survey on vision transformer.IEEE Transactions on Pattern Analysis and Machine Intelligence, PP:1–1, 2020

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:19.209885Z

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Observation 5bb4cde9-e9e6-4cbf-b3be-307a310330c5 · outbound

This paper cites Reddy, Balaswamy Chintha- guntla, Senthil Jagatheesaperumal, Silvia Gaftandzhieva, and Rositsa Doneva.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Reddy, Balaswamy Chintha- guntla, Senthil Jagatheesaperumal, Silvia Gaftandzhieva, and Rositsa Doneva

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:19.329328Z

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Observation d3601f51-5ef0-49ee-a644-3f0293af11a3 · outbound

This paper cites Deblurgan: Blind mo- tion deblurring using conditional adversarial networks.ArXiv e-prints, 2017.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Deblurgan: Blind mo- tion deblurring using conditional adversarial networks.ArXiv e-prints, 2017

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:19.443907Z

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Observation 0ba46fb0-e2e6-4af3-81a0-37b6658ffab6 · outbound

This paper cites Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:19.571792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e0bc17c-63ee-4f2f-8e82-b45f6fe4d9a4 · outbound

This paper cites Recording and playback of camera shake: Benchmarking blind deconvolution with a real-world database.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Recording and playback of camera shake: Benchmarking blind deconvolution with a real-world database

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:19.695588Z

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Observation 9d6e5300-5132-48cb-8054-275d54c31dd8 · outbound

This paper cites Swinir: Image restoration using swin transformer.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Swinir: Image restoration using swin transformer

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:19.806058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7e6f378-e024-4a78-bf32-32bb6856c5e1 · outbound

This paper cites De- blurdinat: A lightweight and effective transformer for image deblurring, 2024.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring De- blurdinat: A lightweight and effective transformer for image deblurring, 2024

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:19.952158Z

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Unavailable: canonical work link unavailable.

Observation d1f21735-27d3-40c1-9951-7802b1f686c1 · outbound

This paper cites Intriguing findings of frequency selection for image deblurring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Intriguing findings of frequency selection for image deblurring

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:20.111047Z

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Unavailable: canonical work link unavailable.

Observation 1836de59-7b71-48bd-ab7e-a97c71317438 · outbound

This paper cites Deep multi-scale convolutional neural network for dynamic scene deblurring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Deep multi-scale convolutional neural network for dynamic scene deblurring

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:20.237201Z

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Unavailable: canonical work link unavailable.

Observation 53947133-a54d-42c7-8396-4688327a7840 · outbound

This paper cites Deep multi-scale convolutional neural network for dynamic scene deblurring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Deep multi-scale convolutional neural network for dynamic scene deblurring

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:20.360540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 761a9e11-a469-4acc-bbeb-7f4d2e63bebb · outbound

This paper cites Multi-temporal recurrent neural networks for progres- sive non-uniform single image deblurring with incremental temporal training.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Multi-temporal recurrent neural networks for progres- sive non-uniform single image deblurring with incremental temporal training

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:20.483499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a41c455-0906-4424-b2cf-ce75bbea3fc4 · outbound

This paper cites Rajagopalan, and Vishnu Boddeti.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Rajagopalan, and Vishnu Boddeti

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:20.599583Z

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Unavailable: canonical work link unavailable.

Observation 2f4c9410-113c-4fc5-b69f-0fd0676b904c · outbound

This paper cites Global filter networks for image classification.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Global filter networks for image classification

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:20.722245Z

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Unavailable: canonical work link unavailable.

Observation 80f0b0a9-f4d8-4d54-a25c-f62831644638 · outbound

This paper cites Real-world blur dataset for learning and benchmarking deblur- ring algorithms.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Real-world blur dataset for learning and benchmarking deblur- ring algorithms

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:20.834394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c72d863-030f-4a0b-a5bc-7c5426d709df · outbound

This paper cites Human-aware motion deblur- ring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Human-aware motion deblur- ring

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:20.982047Z

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Observation 51f9c8de-03b6-4870-81b9-a915c872f4b0 · outbound

This paper cites Scale-recurrent network for deep image deblurring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Scale-recurrent network for deep image deblurring

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:21.118480Z

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Unavailable: canonical work link unavailable.

Observation 4ea94834-15e0-4929-b910-d4b35995c282 · outbound

This paper cites Stripformer: Strip transformer for fast image deblurring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Stripformer: Strip transformer for fast image deblurring

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:21.287972Z

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Observation 8098d88f-f0e9-4cf1-9b81-501bde959dc7 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:21.411631Z

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Observation 220f8c30-3401-44b8-b30f-b4e414721e77 · outbound

This paper cites A fast algorithm for image deblurring with total variation regularization.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring A fast algorithm for image deblurring with total variation regularization

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:21.537234Z

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Observation d5ba1de6-f684-4167-bfa8-93c7d5a540bc · outbound

This paper cites an unresolved cited work.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Unresolved cited work

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:21.686799Z

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Observation 584a33b4-b163-4842-9bd1-0f419164b2ad · outbound

This paper cites Two-phase kernel estimation for ro- bust motion deblurring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Two-phase kernel estimation for ro- bust motion deblurring

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:21.843847Z

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Unavailable: canonical work link unavailable.

Observation f78959cd-e846-479c-a799-12dfe255f856 · outbound

This paper cites Inverted residual fourier transformation for lightweight single image deblurring.IEEE Access, 11:29175–29182, 2023.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Inverted residual fourier transformation for lightweight single image deblurring.IEEE Access, 11:29175–29182, 2023

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:22.005948Z

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Unavailable: canonical work link unavailable.

Observation e5dc3fcf-b6d8-41dd-b514-a8ee2a65e5ff · outbound

This paper cites FDA: Fourier Domain Adaptation for Semantic Segmentation.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring FDA: Fourier Domain Adaptation for Semantic Segmentation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:22.171966Z

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Unavailable: canonical work link unavailable.

Observation 4a57b612-797d-46ba-8f6e-1af8caa5af9a · outbound

This paper cites Multi-stage progressive image restoration.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Multi-stage progressive image restoration

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:22.336690Z

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Observation ba7e72d6-e120-4e4f-a781-757446ad580f · outbound

This paper cites Restormer: Efficient transformer for high-resolution image restoration.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Restormer: Efficient transformer for high-resolution image restoration

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:22.472143Z

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Observation ff5478ee-e67b-40e8-b02e-41164c28e1d6 · outbound

This paper cites Event-guided multi-patch network with self-supervision for non-uniform motion deblurring.In- ternational Journal of Computer Vision, pages 1–18, 2022.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Event-guided multi-patch network with self-supervision for non-uniform motion deblurring.In- ternational Journal of Computer Vision, pages 1–18, 2022

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:22.624508Z

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Unavailable: canonical work link unavailable.

Observation c7d4a41c-4fd1-4626-92b7-15ab8f49c767 · outbound

This paper cites Deblurring by realistic blurring.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Deblurring by realistic blurring

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:22.771704Z

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Unavailable: canonical work link unavailable.

Observation 8fe1ddf0-b128-4883-a9aa-774c16174307 · outbound

This paper cites Image super-resolution using very deep residual channel attention networks.

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring Image super-resolution using very deep residual channel attention networks

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T22:24:22.920907Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.