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Paper Citation Record · LEDGER

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration

As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.19770.

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

pith.paper-citation-record.v1
2507.19770 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:07:35.161321Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation da14acb3-1dc3-46d5-9837-f3270c47bd6c · outbound

This paper cites Portraitpro 24.https : / / www.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Portraitpro 24.https : / / www

Reference 1

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Observation 1ae6f270-2e03-4d23-81a3-b96d70f89736 · outbound

This paper cites an unresolved cited work.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Unresolved cited work

Reference 2

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Observation 21febefc-a07c-46c9-8497-86b352ad00ad · outbound

This paper cites Detecting facial retouching using supervised deep learning.IEEE Transactions on Information Forensics and Security, 11(9):1903–1913, 2016.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Detecting facial retouching using supervised deep learning.IEEE Transactions on Information Forensics and Security, 11(9):1903–1913, 2016

Reference 3

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Observation 778d3db5-95ff-4ffa-8821-d09e93d10fc5 · outbound

This paper cites A Survey on Mixture of Experts in Large Language Models.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration A Survey on Mixture of Experts in Large Language Models

Reference 4

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Source-reported events for the cited work

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Observation cd28f585-8863-4477-96cd-5c29da76440c · outbound

This paper cites An aug- mented lagrangian method for total variation video restora- tion.IEEE Transactions on Image Processing, 20(11):3097– 3111, 2011.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration An aug- mented lagrangian method for total variation video restora- tion.IEEE Transactions on Image Processing, 20(11):3097– 3111, 2011

Reference 5

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Source-reported events for the cited work

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Observation 0484744f-5b49-4f8a-9259-dea13ea9a348 · outbound

This paper cites Pairedcyclegan: Asymmetric style transfer for apply- ing and removing makeup.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Pairedcyclegan: Asymmetric style transfer for apply- ing and removing makeup

Reference 6

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Source-reported events for the cited work

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Observation a030ff06-92e4-4ae0-801d-c9a09e62d58e · outbound

This paper cites Auto- matic facial makeup detection with application in face recog- nition.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Auto- matic facial makeup detection with application in face recog- nition

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2adbe6f8-d21c-4326-bbc0-122201f4f0d5 · outbound

This paper cites Makeup- go: Blind reversion of portrait edit.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Makeup- go: Blind reversion of portrait edit

Reference 8

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Source-reported events for the cited work

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Observation b24f4ffb-c6b9-46b2-9307-76ba5d69688c · outbound

This paper cites Truth in advertising act of 2014, 2014.https://www.congress.gov/bill/ 113th-congress/house-bill/4341.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Truth in advertising act of 2014, 2014.https://www.congress.gov/bill/ 113th-congress/house-bill/4341

Reference 9

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Observation 2ee3788d-5642-40f7-bc2c-624bd10a6a43 · outbound

This paper cites Attentional feature fusion.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Attentional feature fusion

Reference 10

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Source-reported events for the cited work

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Observation d50e4125-480a-41bb-8f9d-7ebcfe5a27a5 · outbound

This paper cites an unresolved cited work.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Unresolved cited work

Reference 11

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Source-reported events for the cited work

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Observation 28ed7059-42b8-469f-9aa4-5e7d32fd3b06 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Arcface: Additive angular margin loss for deep face recognition

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4674eb4d-3c53-4bbc-a0d5-b0f6c17b63e5 · outbound

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

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 13

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Observation d19bbb9d-4edc-4cf3-96a4-97ba55025e73 · outbound

This paper cites The marketing control act.https: //www.forbrukertilsynet.no/english/the- marketing-control-act, 2021.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration The marketing control act.https: //www.forbrukertilsynet.no/english/the- marketing-control-act, 2021

Reference 14

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Source-reported events for the cited work

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Observation 0a45126f-d7df-4d02-b3ee-25420fcddce5 · outbound

This paper cites Ladn: Local adversarial disentangling net- work for facial makeup and de-makeup.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Ladn: Local adversarial disentangling net- work for facial makeup and de-makeup

Reference 15

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Source-reported events for the cited work

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Observation f1fd17b2-a305-479c-9871-b8dcbf46b9de · outbound

This paper cites Vqfr: Blind face restoration with vector-quantized dictionary and parallel de- coder.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Vqfr: Blind face restoration with vector-quantized dictionary and parallel de- coder

Reference 16

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Source-reported events for the cited work

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Observation d08e93fa-9933-4522-a073-0b5a66aecaa7 · outbound

This paper cites Deep residual learning for image recognition.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Deep residual learning for image recognition

Reference 17

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Observation aa86ea30-550a-4cff-ae9b-5de4b4104ff3 · outbound

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

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 18

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Observation c7a2aec4-5748-4907-b4b9-d729ac76064a · outbound

This paper cites Image-to-image translation with conditional adver- sarial networks.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Image-to-image translation with conditional adver- sarial networks

Reference 19

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Unavailable: canonical work link unavailable.

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Observation 67be797d-c42b-4f7b-a3ef-18f31590320b · outbound

This paper cites Detecting gans and retouching based digital alter- ations via dad-hcnn.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Detecting gans and retouching based digital alter- ations via dad-hcnn

Reference 20

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Source-reported events for the cited work

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Observation ba4c06a1-129d-48c5-821f-0d6afc0b05d6 · outbound

This paper cites Hierarchical mixtures of experts and the em algorithm.Neural computation, 6(2): 181–214, 1994.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Hierarchical mixtures of experts and the em algorithm.Neural computation, 6(2): 181–214, 1994

Reference 21

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Observation 688616b0-3f35-41e8-a59a-93c63a4c8d9b · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration A style-based generator architecture for generative adversarial networks

Reference 22

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Observation ca595406-f85d-4a8d-b3a4-3fd4932c2cdd · outbound

This paper cites Pasd: A performance analysis approach through the statistical debugging of kernel events.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Pasd: A performance analysis approach through the statistical debugging of kernel events

Reference 23

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Source-reported events for the cited work

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Observation 2b6ae628-1349-412d-b6c3-4f8c09a10a35 · outbound

This paper cites Adaface: Quality adaptive margin for face recognition.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Adaface: Quality adaptive margin for face recognition

Reference 24

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Observation a6678328-21ae-4a39-8551-259ec31e534e · outbound

This paper cites Adam: A Method for Stochastic Optimization.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Adam: A Method for Stochastic Optimization

Reference 25

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Observation f17c23dc-1bf2-445e-a14c-7a30e5b92a1a · outbound

This paper cites Blind face restoration via deep multi-scale component dictionaries.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Blind face restoration via deep multi-scale component dictionaries

Reference 26

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Observation 0802efd4-5d7e-44ae-a293-3f7ef4eb6245 · outbound

This paper cites Diff- bir: Toward blind image restoration with generative diffusion prior.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Diff- bir: Toward blind image restoration with generative diffusion prior

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a05bd6e7-6bb2-4924-b56f-ea48e3d8a665 · outbound

This paper cites DeepSeek-V3 Technical Report.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration DeepSeek-V3 Technical Report

Reference 28

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Source-reported events for the cited work

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Observation 2c375dfd-7ebd-4b03-8969-13f5b961c8d7 · outbound

This paper cites Psgan++: Robust detail-preserving makeup transfer and removal.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 44(11):8538–8551,.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Psgan++: Robust detail-preserving makeup transfer and removal.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 44(11):8538–8551,

Reference 29

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Source-reported events for the cited work

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Observation b841ad5e-ad7d-47e4-975f-78ccedbbfca3 · outbound

This paper cites Supermodels without photoshop: Israel’s ‘pho- toshop law’ puts focus on digitally altered images, 2015.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Supermodels without photoshop: Israel’s ‘pho- toshop law’ puts focus on digitally altered images, 2015

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c953cede-ed98-44bc-a590-70978339ef50 · outbound

This paper cites Prnu-based detection of facial retouching.IET Bio- metrics, 9(4):154–164, 2020.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Prnu-based detection of facial retouching.IET Bio- metrics, 9(4):154–164, 2020

Reference 31

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Source-reported events for the cited work

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Observation b0881613-5f74-4198-9920-8794fef044c1 · outbound

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

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration U- net: Convolutional networks for biomedical image segmen- tation

Reference 32

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Source-reported events for the cited work

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Observation dd51c241-7e63-43d6-9e1d-edf057c919d8 · outbound

This paper cites Resdiff: Combining cnn and diffusion model for image super-resolution.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Resdiff: Combining cnn and diffusion model for image super-resolution

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation dffd6bb1-2cf4-4fc7-90d4-a8e1407bfd4c · outbound

This paper cites Denoising Diffusion Implicit Models.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Denoising Diffusion Implicit Models

Reference 34

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unresolved
no resolver link, observed 2026-08-06T14:07:35.139988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:07:35.139988Z digest=sha256:8ddc53c22f143849c9f95963e8b907fa1cb60c747c667dc738c07a514065ecf6

Observation b8afcc5c-c7d7-46b3-8439-21fcda99b396 · outbound

This paper cites Ssat: A symmetric semantic-aware transformer network for makeup transfer and removal.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Ssat: A symmetric semantic-aware transformer network for makeup transfer and removal

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:07:35.285287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:07:35.142752Z digest=sha256:9c7e6e51f512ba718abac9dbb75045459e4d8fd3e2aae2f3ffcf7dec097a0166

Observation 102fadd6-b9f3-4b2f-bc52-5183aba43e02 · outbound

This paper cites Content-style decoupling for unsupervised makeup transfer without generating pseudo ground truth.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Content-style decoupling for unsupervised makeup transfer without generating pseudo ground truth

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:07:35.277856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:07:35.145183Z digest=sha256:f15b0503f52a4c6b6f7107ff3c57c71554efc32b8fbb82e7371633f3b1717ca3

Observation 932da657-d187-48d1-bb48-f55595e9d88f · outbound

This paper cites Face behind makeup.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Face behind makeup

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:07:35.269955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:07:35.147423Z digest=sha256:849454409980df04c26817412ef48f8e38401d46d72b056df22fe3967e9298ca

Observation 1cc43bd0-3ec4-4cfd-a26f-de559fc197ec · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:07:35.262159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:07:35.149844Z digest=sha256:001d5d5459b8d011e3a147e3534b17d3e4696c32046cadbf70ee41c92e6bc442

Observation f56ff618-2d47-491c-868e-e1641511c8ff · outbound

This paper cites Restoreformer++: Towards real- world blind face restoration from undegraded key-value pairs.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Restoreformer++: Towards real- world blind face restoration from undegraded key-value pairs.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:07:35.254467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:07:35.152076Z digest=sha256:eefb91f554ac7b36c2171bff96a85297f15d0a8a6472752e602a174b0495759c

Observation 4c5b2224-89b8-4790-9503-99decbc26073 · outbound

This paper cites Dr2: Diffusion-based robust degradation remover for blind face restoration.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Dr2: Diffusion-based robust degradation remover for blind face restoration

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:07:35.246883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:07:35.154445Z digest=sha256:6b99d81b21e8ebf38798ba003dc41e6a1825a941de601b63b43f125a552372d2

Observation 2f0f1839-66e9-4f31-bce5-0913bfa5ff61 · outbound

This paper cites One-step effective diffusion network for real-world image super-resolution.Advances in Neural Information Process- ing Systems, 37:92529–92553, 2024.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration One-step effective diffusion network for real-world image super-resolution.Advances in Neural Information Process- ing Systems, 37:92529–92553, 2024

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:07:35.238868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:07:35.156776Z digest=sha256:9eedcc36052cbd2b3516c611ebfc636bcd709555d27d818d844e1fa5450ae28f

Observation 4aa6d66f-5f8d-477f-b1d0-6e4027bdc4b2 · outbound

This paper cites Retouchingffhq: A large-scale dataset for fine-grained face retouching detection.

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Retouchingffhq: A large-scale dataset for fine-grained face retouching detection

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:07:35.230387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:07:35.159094Z digest=sha256:0df2a71b919482d8c0c54550ff95327aa3ca682e953f28b2cf655fdf1040fe6b

Observation bc7f3f8e-9d1c-45cf-9441-0a3781a7b52b · outbound

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

MoFRR: Mixture of Diffusion Models for Face Retouching Restoration Restormer: Efficient transformer for high-resolution image restoration

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T14:07:35.161321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:07:35.161321Z digest=sha256:8ca8f3825cba82861454559d631dc3ce8741a2b81ec81620fc7e817519fcbb86

Pith citing papers

No inbound Pith citation observations are available.