Paper Citation Record · LEDGER

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision

As of 17 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2606.06176.

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

pith.paper-citation-record.v1
2606.06176 v1

Coverage vector

measured 37 of 37 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-06-28T02:49:23.870076Z

measured 37 of 37 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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Outbound references

Observation f7d12fcf-3eaf-4f6d-9e3f-11fbb8fa8d81 · outbound

This paper cites A revised underwater image formation model.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision A revised underwater image formation model

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Unavailable: canonical work link unavailable.

Observation c0d11479-b412-4a04-9b3e-03e87a706d66 · outbound

This paper cites Sea-thru: A method for removing water from underwater images.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Sea-thru: A method for removing water from underwater images

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 9bde6809-d4e0-43a9-99b1-bd453f9e0453 · outbound

This paper cites Unveiling the under- water world: Clip perception model-guided underwater im- age enhancement.Pattern Recognition, 162:111395, 2025.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Unveiling the under- water world: Clip perception model-guided underwater im- age enhancement.Pattern Recognition, 162:111395, 2025

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation ced878e1-e0e5-43b5-b11f-29d2e8690589 · outbound

This paper cites Underwater image en- hancement by wavelength compensation and dehazing.IEEE transactions on image processing, 21(4):1756–1769, 2011.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Underwater image en- hancement by wavelength compensation and dehazing.IEEE transactions on image processing, 21(4):1756–1769, 2011

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation a30191fd-23ff-45c9-b2bd-31944c5c9dfb · outbound

This paper cites Pugan: Physi- cal model-guided underwater image enhancement using gan with dual-discriminators.IEEE Transactions on Image Pro- cessing, 32:4472–4485, 2023.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Pugan: Physi- cal model-guided underwater image enhancement using gan with dual-discriminators.IEEE Transactions on Image Pro- cessing, 32:4472–4485, 2023

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 6e69175c-1062-4b99-bb21-02f75dc4dec6 · outbound

This paper cites Underwater depth estimation and image restoration based on single im- ages.IEEE computer graphics and applications, 36(2):24– 35, 2016.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Underwater depth estimation and image restoration based on single im- ages.IEEE computer graphics and applications, 36(2):24– 35, 2016

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Unavailable: canonical work link unavailable.

Observation 1bcba287-aab9-41e0-8d39-db16b1391f0d · outbound

This paper cites Twice mixing: A rank learning based quality assessment ap- proach for underwater image enhancement.Signal Process- ing: Image Communication, 102:116622, 2022.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Twice mixing: A rank learning based quality assessment ap- proach for underwater image enhancement.Signal Process- ing: Image Communication, 102:116622, 2022

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation b2de21c9-c865-4914-9890-8f882c6ad012 · outbound

This paper cites Fine-tuning image-conditional diffusion models is easier than you think.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Fine-tuning image-conditional diffusion models is easier than you think

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 4b4c3730-bb30-44d2-a603-6fe252932c9d · outbound

This paper cites A survey on underwater computer vision.ACM Computing Surveys, 55(13s):1–39, 2023.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision A survey on underwater computer vision.ACM Computing Surveys, 55(13s):1–39, 2023

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation d1b3e8b1-f0ef-4e98-8ce7-f5c762fd9464 · outbound

This paper cites Underwater ranker: Learn which is better and how to be better.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Underwater ranker: Learn which is better and how to be better

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation aba28c6d-7153-43d0-b3d6-cf7376bbd86a · outbound

This paper cites Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 498a9043-4145-49be-9297-04b218bb34f1 · outbound

This paper cites Underwater sequential images enhancement via diffusion and physics priors fusion.Information Fusion, page 103365,.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Underwater sequential images enhancement via diffusion and physics priors fusion.Information Fusion, page 103365,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 9477aa32-a221-4e6c-a054-cfba14b315b5 · outbound

This paper cites Contrastive semi-supervised learning for underwa- ter image restoration via reliable bank.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Contrastive semi-supervised learning for underwa- ter image restoration via reliable bank

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Unavailable: canonical work link unavailable.

Observation 0330c0ce-8457-441a-8a3e-d9bd39b62bee · outbound

This paper cites Fast un- derwater image enhancement for improved visual percep- tion.IEEE Robotics and Automation Letters, 5(2):3227– 3234, 2020.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Fast un- derwater image enhancement for improved visual percep- tion.IEEE Robotics and Automation Letters, 5(2):3227– 3234, 2020

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation d14b46ad-96c9-41d5-9732-ee25486c1f40 · outbound

This paper cites Computer modeling and the design of opti- mal underwater imaging systems.IEEE Journal of Oceanic Engineering, 15(2):101–111, 1990.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Computer modeling and the design of opti- mal underwater imaging systems.IEEE Journal of Oceanic Engineering, 15(2):101–111, 1990

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 0c402672-f0b4-4947-9fa9-4bf905100538 · outbound

This paper cites Five A$^{+}$ Network: You Only Need 9K Parameters for Underwater Image Enhancement.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Five A$^{+}$ Network: You Only Need 9K Parameters for Underwater Image Enhancement

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:56:55.049224Z

Source-reported events for the cited work

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Observation e34b0dd6-593a-4f5c-a7f2-e2060ad80edb · outbound

This paper cites Repurpos- ing diffusion-based image generators for monocular depth estimation.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation c0eab4e7-7fbf-4c67-a204-5cfab03235fd · outbound

This paper cites Musiq: Multi-scale image quality transformer.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Musiq: Multi-scale image quality transformer

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation f8bedaba-9f5f-475d-b35a-fd3affeab4e4 · outbound

This paper cites Rad: Region-aware diffusion models for image inpainting.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Rad: Region-aware diffusion models for image inpainting

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation a1fbf0a4-158d-4cff-a365-403225b071ba · outbound

This paper cites Auto-Encoding Variational Bayes.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Auto-Encoding Variational Bayes

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:56:55.046806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8f9b9299-3214-4fcc-baba-ff3bb37e3b59 · outbound

This paper cites An underwater image enhancement benchmark dataset and beyond.IEEE transac- tions on image processing, 29:4376–4389, 2019.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision An underwater image enhancement benchmark dataset and beyond.IEEE transac- tions on image processing, 29:4376–4389, 2019

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 18be44a0-e4fc-4f83-8257-52d6eba5bcf6 · outbound

This paper cites Underwater image enhance- ment via medium transmission-guided multi-color space em- bedding.IEEE Transactions on Image Processing, 30:4985– 5000, 2021.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Underwater image enhance- ment via medium transmission-guided multi-color space em- bedding.IEEE Transactions on Image Processing, 30:4985– 5000, 2021

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 896b0ba3-d315-450c-92bf-07b1f8604d28 · outbound

This paper cites Underwater image enhancement with cascaded con- trastive learning.IEEE Transactions on Multimedia, 2024.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Underwater image enhancement with cascaded con- trastive learning.IEEE Transactions on Multimedia, 2024

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 9929ab02-ad2f-430d-ace7-ad6bd74ea23e · outbound

This paper cites Visual-instructed degradation diffusion for all-in-one image restoration.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Visual-instructed degradation diffusion for all-in-one image restoration

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation cf5f6a0c-e17f-4c00-b60d-dd938cef3b13 · outbound

This paper cites A computer model for underwater camera systems.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision A computer model for underwater camera systems

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation e410727c-46c2-40fb-95f7-651967f475d1 · outbound

This paper cites Dpf-net: Physical imaging model embedded data-driven underwater image enhancement.ISPRS Jour- nal of Photogrammetry and Remote Sensing, 228:679–693,.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Dpf-net: Physical imaging model embedded data-driven underwater image enhancement.ISPRS Jour- nal of Photogrammetry and Remote Sensing, 228:679–693,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 6c6aa0c0-1ac4-4d4f-a791-a595b77ce855 · outbound

This paper cites Human-visual- system-inspired underwater image quality measures.IEEE Journal of Oceanic Engineering, 41(3):541–551, 2015.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Human-visual- system-inspired underwater image quality measures.IEEE Journal of Oceanic Engineering, 41(3):541–551, 2015

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 7cea9694-7e49-4a57-a724-85e84d119aad · outbound

This paper cites Adaptive dual-domain learn- ing for underwater image enhancement.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Adaptive dual-domain learn- ing for underwater image enhancement

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation aedfe792-fe1b-423f-a082-a3d4084e5751 · outbound

This paper cites Ce-vae: Capsule enhanced variational autoencoder for underwater image enhancement.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Ce-vae: Capsule enhanced variational autoencoder for underwater image enhancement

Reference 29

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Observation 46d01721-9ecc-49f1-a3e7-ec3f10aad029 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision High-resolution image synthesis with latent diffusion models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 010067f0-2c50-479d-9c3d-17eae6635e67 · outbound

This paper cites Denoising Diffusion Implicit Models.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Denoising Diffusion Implicit Models

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:56:55.041640Z

Source-reported events for the cited work

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Observation b2782216-fae0-495b-bbc1-7a4aa2bc3782 · outbound

This paper cites Uveb: A large-scale bench- mark and baseline towards real-world underwater video en- hancement.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Uveb: A large-scale bench- mark and baseline towards real-world underwater video en- hancement

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 0544d808-5800-4f5b-b3b4-7baa8c06ddba · outbound

This paper cites Style-Decoupled Adaptive Routing Network for Underwater Image Enhancement.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Style-Decoupled Adaptive Routing Network for Underwater Image Enhancement

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:56:55.044624Z

Source-reported events for the cited work

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Observation 0018239d-806b-4f42-b9bc-6ec51dba02e1 · outbound

This paper cites Underwater image enhance- ment via minimal color loss and locally adaptive contrast en- hancement.IEEE Transactions on Image Processing, 31: 3997–4010, 2022.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Underwater image enhance- ment via minimal color loss and locally adaptive contrast en- hancement.IEEE Transactions on Image Processing, 31: 3997–4010, 2022

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation 3210ed3b-0cc0-4e09-b11d-8c216155bd5b · outbound

This paper cites Wavelet-based fourier information interaction with fre- quency diffusion adjustment for underwater image restora- tion.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Wavelet-based fourier information interaction with fre- quency diffusion adjustment for underwater image restora- tion

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Observation f9b5c3a4-94b3-4a0e-ada8-782e67bdddd1 · outbound

This paper cites an unresolved cited work.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Unresolved cited work

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Unavailable: canonical work link unavailable.

Observation 0228fa7b-db9e-4c39-98ad-8fb68ad8678d · outbound

This paper cites Underwater image enhancement with hyper-laplacian re- flectance priors.IEEE Transactions on Image Processing, 31:5442–5455, 2022.

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision Underwater image enhancement with hyper-laplacian re- flectance priors.IEEE Transactions on Image Processing, 31:5442–5455, 2022

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-28T02:49:23.870076Z

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Unavailable: canonical work link unavailable.

Pith citing papers

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