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Paper Citation Record · LEDGER

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training

As of 8 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2507.09524.

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

pith.paper-citation-record.v1
2507.09524 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:58:44.344482Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

51 of 51 outbound references displayed

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  • verified fuzzy39
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ab882b7f-edd3-4112-9799-691d2b170f04 · outbound

This paper cites I-haze: A dehazing bench- mark with real hazy and haze-free indoor images.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training I-haze: A dehazing bench- mark with real hazy and haze-free indoor images

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5b2c26b6-483d-49f4-94f5-4a58b0883711 · outbound

This paper cites O-haze: a dehazing bench- mark with real hazy and haze-free outdoor images.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training O-haze: a dehazing bench- mark with real hazy and haze-free outdoor images

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e046eff2-11a5-4474-b843-66c56d51dcd1 · outbound

This paper cites Non-local image dehazing.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Non-local image dehazing

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 97163cf8-76f8-4bc8-a415-0052ed91cddd · outbound

This paper cites Dehazenet: An end-to-end system for single image haze removal.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Dehazenet: An end-to-end system for single image haze removal

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 02743045-81b2-4039-b663-423ced70e726 · outbound

This paper cites Psd: Principled synthetic-to-real dehazing guided by physi- cal priors.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Psd: Principled synthetic-to-real dehazing guided by physi- cal priors

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4654eec0-bb31-4280-ba6c-1131527765d4 · outbound

This paper cites Dea-net: Single image dehazing based on detail-enhanced convolution and content-guided attention.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Dea-net: Single image dehazing based on detail-enhanced convolution and content-guided attention

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6970dd7d-80e5-4b39-9b63-69e143893a9b · outbound

This paper cites Multi-scale boosted de- hazing network with dense feature fusion.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Multi-scale boosted de- hazing network with dense feature fusion

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6c92f8ae-843b-433b-b197-ad0efb582e75 · outbound

This paper cites Cunsb-rfie: Context-aware unpaired neural schrodinger bridge in retinal fundus image enhancement.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Cunsb-rfie: Context-aware unpaired neural schrodinger bridge in retinal fundus image enhancement

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b94e7b0d-526b-422c-8f99-fa64053425b0 · outbound

This paper cites Cycle- dehaze: Enhanced cyclegan for single image dehazing.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Cycle- dehaze: Enhanced cyclegan for single image dehazing

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation eadbd3b6-6b3a-4d53-b1f5-0ed6e481c615 · outbound

This paper cites Guided real image dehazing using ycbcr color space.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Guided real image dehazing using ycbcr color space

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 091b6fc9-6fbc-4c19-a3d3-c19bfd0b2977 · outbound

This paper cites Yolov3: An incremental improvement.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Yolov3: An incremental improvement

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e613dc73-ba52-4d6b-ae02-39e22a8def17 · outbound

This paper cites Dehazing using color-lines.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Dehazing using color-lines

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4e46ece6-261a-4541-bda6-8ac1420f1527 · outbound

This paper cites Advancing real-world image dehazing: perspective, modules, and training.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Advancing real-world image dehazing: perspective, modules, and training

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fdaf5623-fb21-40c2-a5e8-063af5065dca · outbound

This paper cites Generative adversarial networks.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Generative adversarial networks

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c9afdfd2-12d1-40d7-aac9-48ea98ada9ed · outbound

This paper cites Onerestore: A universal restoration frame- work for composite degradation.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Onerestore: A universal restoration frame- work for composite degradation

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a22a8169-7513-41b1-ba50-c3b448a37f9a · outbound

This paper cites Single image haze removal using dark channel prior.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Single image haze removal using dark channel prior

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f3a94ef1-d256-499d-8da6-e0cb2fe78099 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 17

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Source-reported events for the cited work

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Observation 06e74ac8-ba69-4e51-8f5d-f9f2503143eb · outbound

This paper cites Denoising dif- fusion probabilistic models.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Denoising dif- fusion probabilistic models

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d7fb9948-4d2a-4293-a957-5192b5d25ad6 · outbound

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

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Musiq: Multi-scale image quality transformer

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation cafd0eb0-8146-467d-9d5b-aae369197aea · outbound

This paper cites Unpaired image-to-image translation via neu- ral schr¨odinger bridge.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Unpaired image-to-image translation via neu- ral schr¨odinger bridge

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1595b939-f96d-4ce9-be72-969a519b4499 · outbound

This paper cites Ensembling off-the-shelf models for gan training.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Ensembling off-the-shelf models for gan training

Reference 21

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Source-reported events for the cited work

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Observation 7cf743de-2c52-4881-9d33-9ebbd1804ce4 · outbound

This paper cites Exploiting diffusion prior for real-world image dehazing with unpaired training.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Exploiting diffusion prior for real-world image dehazing with unpaired training

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6e7843d4-b411-47bb-8805-9f4ac233f454 · outbound

This paper cites Benchmarking single- image dehazing and beyond.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Benchmarking single- image dehazing and beyond

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f23ce791-b2cb-4010-a483-9d5cc01a1690 · outbound

This paper cites You only look yourself: Un- supervised and untrained single image dehazing neural net- work.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training You only look yourself: Un- supervised and untrained single image dehazing neural net- work

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c2d5064e-2163-4652-9cb2-3f50ece921dc · outbound

This paper cites USTC-TD: A Test Dataset and Benchmark for Image and Video Coding in 2020s.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training USTC-TD: A Test Dataset and Benchmark for Image and Video Coding in 2020s

Reference 25

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9c56c268-9668-4f76-bd0b-76d37152be5b · outbound

This paper cites Iterative prompt learning for unsupervised backlit image enhancement.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Iterative prompt learning for unsupervised backlit image enhancement

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 72e4bf88-6ca8-460d-9111-d706c762f61d · outbound

This paper cites Theodorou, Weili Nie, and Anima Anandkumar.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Theodorou, Weili Nie, and Anima Anandkumar

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:49.076024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0bc1374e-8a9f-46d8-b12a-64e4b82e33df · outbound

This paper cites Diff-plugin: Revitalizing details for diffusion-based low-level tasks.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Diff-plugin: Revitalizing details for diffusion-based low-level tasks

Reference 28

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ff0cd443-4c8d-452d-960d-5ca9dee81221 · outbound

This paper cites completely blind.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training completely blind

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:48.588296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b8e29a02-640a-4c65-ae96-59a1d436168c · outbound

This paper cites Unsupervised image prior via prompt learning and clip se- mantic guidance for low-light image enhancement.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Unsupervised image prior via prompt learning and clip se- mantic guidance for low-light image enhancement

Reference 30

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raw_fallback, observed 2026-08-06T17:58:48.322058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d970026f-b166-4c30-94be-088eb2c6e42d · outbound

This paper cites Vision in bad weather.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Vision in bad weather

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0509acfe-216d-4272-8970-90a978a00db6 · outbound

This paper cites Contrastive learning for unpaired image-to-image translation.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Contrastive learning for unpaired image-to-image translation

Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 24e285fe-8fab-48c1-b20c-6efdd29fd434 · outbound

This paper cites Mb-taylorformer: Multi-branch efficient transformer expanded by taylor formula for image dehazing.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Mb-taylorformer: Multi-branch efficient transformer expanded by taylor formula for image dehazing

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:58:42.088011Z digest=sha256:388e59ee04ab7efe8b760f8110a8d38cd0c1c071d917fe23c92f7eaf98882c0c

Observation ed94fc19-19e5-43c7-8579-48a172f0cf9e · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Learning Transferable Visual Models From Natural Language Supervision

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-06T17:58:47.149079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation dbe8ce4e-6d6c-4edc-a21b-13ff85ad7c7c · outbound

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

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training High-resolution image synthesis with latent diffusion models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T17:58:42.305254Z

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Unavailable: canonical work link unavailable.

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Observation 8af84b09-e2b6-4f9a-b6b0-62932d3e1834 · outbound

This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training U- net: Convolutional networks for biomedical image segmen- tation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T17:58:42.387845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7914a9da-bd19-4a9c-916a-a3fd1115288b · outbound

This paper cites Sur la th ´eorie relativiste de l’´electron et l’interpr´etation de la m ´ecanique quantique.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Sur la th ´eorie relativiste de l’´electron et l’interpr´etation de la m ´ecanique quantique

Reference 37

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 20493d77-0ca8-489e-aa08-b9401a0aea1e · outbound

This paper cites Domain adaptation for image dehazing.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Domain adaptation for image dehazing

Reference 38

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a67b0135-4ccb-444d-9123-241c73d602c7 · outbound

This paper cites Denois- ing diffusion implicit models.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Denois- ing diffusion implicit models

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 30edbc3e-c0d3-4871-a13d-743a17f3376a · outbound

This paper cites Ucl-dehaze: Towards real-world image dehazing via unsupervised contrastive learning.IEEE Transactions on Im- age Processing, 2024.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Ucl-dehaze: Towards real-world image dehazing via unsupervised contrastive learning.IEEE Transactions on Im- age Processing, 2024

Reference 40

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 292ffc8b-6484-4110-8413-b02d086eed70 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Image quality assessment: from error visibility to structural similarity

Reference 41

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:58:42.987776Z digest=sha256:ec9160bad2638eb03e29b93f46f0271b74063908d4520288928bcdeb2dce72b5

Observation 7c994245-8bf9-4980-867c-947b6a6e7a1f · outbound

This paper cites Maniqa: Multi-dimension attention network for no-reference image quality assessment.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Maniqa: Multi-dimension attention network for no-reference image quality assessment

Reference 42

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8aa08f6a-f75a-47b8-8241-00396081691b · outbound

This paper cites Self-augmented unpaired image de- hazing via density and depth decomposition.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Self-augmented unpaired image de- hazing via density and depth decomposition

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:45.802712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:58:43.349579Z digest=sha256:1c5c0f13f3e625638ffd2d4b5b037a9459fa5db204611b9b40a1e89b5d15eb1a

Observation a57968a2-a44b-439d-b3c8-d46e980b56c4 · outbound

This paper cites Robust unpaired image dehazing via density and depth de- composition.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Robust unpaired image dehazing via density and depth de- composition

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:45.638968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:58:43.477170Z digest=sha256:312a3d3b1636be3609e9f48867447ab3e315bc76cc7dfe28b865c8040a3e092b

Observation d6a61db8-a79f-4ddb-93af-aa09f3778cbf · outbound

This paper cites Vsi: A visual saliency-induced index for perceptual image quality assess- ment.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Vsi: A visual saliency-induced index for perceptual image quality assess- ment

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:45.474185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:58:43.595996Z digest=sha256:47104e3e0f9a0648aee3e9d836cf56ec8e8fdd61098204fa110acc382b790359

Observation 5e2a502b-80ca-449e-9229-e72b901741ce · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training The unreasonable effectiveness of deep features as a perceptual metric

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T17:58:43.708999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 792a83e2-ec0b-440d-be4e-813ec16a3bb0 · outbound

This paper cites Re- finednet: A weakly supervised refinement framework for sin- gle image dehazing.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Re- finednet: A weakly supervised refinement framework for sin- gle image dehazing

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:45.305086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:58:43.815532Z digest=sha256:45e1f1f0d934134c26a48252990a088315d66e48f37a8a796b6669fc97a86c0b

Observation f527385b-f0c1-48e9-b2af-050c01a40e48 · outbound

This paper cites Curricular contrastive regularization for physics-aware single image dehazing.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Curricular contrastive regularization for physics-aware single image dehazing

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:45.137129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:58:43.921610Z digest=sha256:b2f808cae95b0553faf32a52b6f61273960fafe93c78e028fba3783f1cc777e7

Observation d94e9c0b-f77c-4b30-9533-05342755e64d · outbound

This paper cites Semantic under- standing of scenes through the ade20k dataset.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Semantic under- standing of scenes through the ade20k dataset

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:44.963142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:58:44.055544Z digest=sha256:3b5575a1469a1bb1ed3276db6031273738de5f38c7d6037ebc9aa94f6cf0370c

Observation 15f38def-663d-40d5-9261-c7b91b01f355 · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networks.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training Unpaired image-to-image translation using cycle- consistent adversarial networks

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:58:44.836887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:58:44.183965Z digest=sha256:eb6da75edb2a7f63c319e0f9a893f6e045029be5d1a2116944854ea558cb26d1

Observation 8e9b37a2-301f-4770-ae7c-40257e32b6f8 · outbound

This paper cites A fast single image haze removal algorithm using color attenuation prior.

When Schr\"odinger Bridge Meets Real-World Image Dehazing with Unpaired Training A fast single image haze removal algorithm using color attenuation prior

Reference 51

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unresolved
no resolver link, observed 2026-08-06T17:58:44.344482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.