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Paper Citation Record · LEDGER

Auto-Encoded Supervision for Perceptual Image Super-Resolution

As of 23 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2412.00124.

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

pith.paper-citation-record.v1
2412.00124 v2

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

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measured 70 of 70 standing notices

One-hop event checks from named stored sources.

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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

70 of 70 outbound references displayed

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External citation measurements

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Outbound references

Observation 8f45954c-cd43-4a0d-a508-e1d13c582528 · outbound

This paper cites Ntire 2017 challenge on single image super-resolution: Dataset and study.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Ntire 2017 challenge on single image super-resolution: Dataset and study

Reference 1

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Observation 09e0b12c-8eeb-4e2f-92ec-50d337fa220c · outbound

This paper cites The perception-distortion tradeoff.

Auto-Encoded Supervision for Perceptual Image Super-Resolution The perception-distortion tradeoff

Reference 2

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Observation 7b5f6e73-f21b-4b46-b387-73fe908449a7 · outbound

This paper cites Toward real-world single image super-resolution: A new benchmark and a new model.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Toward real-world single image super-resolution: A new benchmark and a new model

Reference 3

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Observation 3da0f752-40ba-4176-9b9d-8a8b5d1c7dad · outbound

This paper cites Any-resolution training for high- resolution image synthesis.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Any-resolution training for high- resolution image synthesis

Reference 4

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Observation 192e0c8c-f17c-4065-a28e-74a37062910e · outbound

This paper cites Pre-trained image processing transformer.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Pre-trained image processing transformer

Reference 5

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Observation 7a620ea0-220f-4ee8-b009-bacbe209aa58 · outbound

This paper cites Activating more pixels in image super- resolution transformer.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Activating more pixels in image super- resolution transformer

Reference 6

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Observation ff7c2c2e-70e8-4ff2-809c-1da6ab49bf3d · outbound

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

Auto-Encoded Supervision for Perceptual Image Super-Resolution Rethinking coarse-to-fine approach in sin- gle image deblurring

Reference 7

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Observation c252e208-6287-43bc-9406-ea6ac3696044 · outbound

This paper cites Selective frequency network for image restoration.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Selective frequency network for image restoration

Reference 8

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Observation 8c5df155-2d9b-48df-99e9-f6e6ff641f0c · outbound

This paper cites Second-order attention network for single im- age super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Second-order attention network for single im- age super-resolution

Reference 9

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Source-reported events for the cited work

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Observation 4ee3a56b-61ff-4fb5-b75c-cd80ab206cc5 · outbound

This paper cites Projected distribution loss for image enhancement.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Projected distribution loss for image enhancement

Reference 10

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Observation af212426-e967-4e19-a741-a3981f8d660f · outbound

This paper cites Wavelet domain style transfer for an effective perception- distortion tradeoff in single image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Wavelet domain style transfer for an effective perception- distortion tradeoff in single image super-resolution

Reference 11

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Observation 4f5b6d9b-94d9-4782-b33a-cdf36c816f60 · outbound

This paper cites Image quality assessment: Unifying structure and tex- ture similarity.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Image quality assessment: Unifying structure and tex- ture similarity

Reference 12

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Observation f7c1158e-3385-41ec-bc54-1ee0d319a00d · outbound

This paper cites Image super-resolution using deep convolutional net- works.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Image super-resolution using deep convolutional net- works

Reference 13

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Observation 86b6f454-1144-4901-a1a3-98993754d44f · outbound

This paper cites Acceler- ating the super-resolution convolutional neural network.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Acceler- ating the super-resolution convolutional neural network

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 65419fd7-4d4e-4e51-8bf0-42cd3b6f34cd · outbound

This paper cites Generative adversarial nets.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Generative adversarial nets

Reference 15

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Observation 90a14ea6-1dfc-4106-9f80-d8d54ef89fe0 · outbound

This paper cites Ode-inspired network design for sin- gle image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Ode-inspired network design for sin- gle image super-resolution

Reference 16

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Source-reported events for the cited work

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Observation 454c7f86-e479-4bd0-a246-071b89a6e1c6 · outbound

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

Auto-Encoded Supervision for Perceptual Image Super-Resolution Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 17

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Observation 380d5365-5661-4fb5-ab59-863b27c3255e · outbound

This paper cites DRCT: Saving Image Super-resolution away from Information Bottleneck.

Auto-Encoded Supervision for Perceptual Image Super-Resolution DRCT: Saving Image Super-resolution away from Information Bottleneck

Reference 18

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Observation 2a4c9d3a-4db4-4607-a2be-018584b13e44 · outbound

This paper cites Single image super-resolution from transformed self-exemplars.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Single image super-resolution from transformed self-exemplars

Reference 19

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Observation 41b232ec-a9f7-4da5-b4c3-2e0d0797b037 · outbound

This paper cites Varsr: Variational super- resolution network for very low resolution images.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Varsr: Variational super- resolution network for very low resolution images

Reference 20

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Source-reported events for the cited work

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Observation 74620ab8-2195-4bd8-abda-33722ffb922a · outbound

This paper cites Variance and bias for general loss func- tions.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Variance and bias for general loss func- tions

Reference 21

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Observation c7af90bb-8057-4a00-8db9-c9b3bc05d2f1 · outbound

This paper cites Percep- tual losses for real-time style transfer and super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Percep- tual losses for real-time style transfer and super-resolution

Reference 22

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Observation 6ab844cf-f02b-4847-a13b-1839d4892211 · outbound

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

Auto-Encoded Supervision for Perceptual Image Super-Resolution A style-based generator architecture for generative adversarial networks

Reference 23

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Observation f62fbb80-f104-445e-b682-8ebee8a620ed · outbound

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

Auto-Encoded Supervision for Perceptual Image Super-Resolution Musiq: Multi-scale image quality transformer

Reference 24

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Observation ea60cb1f-1769-461d-add5-d3681bf40a2c · outbound

This paper cites Accurate image super-resolution using very deep convolutional net- works.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Accurate image super-resolution using very deep convolutional net- works

Reference 25

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ed2ffc59-010f-4641-a0c9-f221e2ee162b · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Adam: A Method for Stochastic Optimization

Reference 26

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Observation 7fed2cfa-3abe-487f-a173-257507ee046d · outbound

This paper cites Sparsity aware nor- malization for gans.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Sparsity aware nor- malization for gans

Reference 27

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Observation 56ffea9a-c425-4a34-8171-198cb9c089d0 · outbound

This paper cites Deep self-dissimilarities as powerful visual finger- prints.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Deep self-dissimilarities as powerful visual finger- prints

Reference 28

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Source-reported events for the cited work

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Observation 584abfaa-47d7-4f45-8a3a-44300df9bb7c · outbound

This paper cites Does Diffusion Beat GAN in Image Super Resolution?.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Does Diffusion Beat GAN in Image Super Resolution?

Reference 29

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Observation c64c7aff-6f73-4223-a8f9-f24addbb2c58 · outbound

This paper cites Photo- realistic single image super-resolution using a generative ad- versarial network.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Photo- realistic single image super-resolution using a generative ad- versarial network

Reference 30

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Observation 3c4bd238-69e6-4ebf-84f2-bf49cba5e5cd · outbound

This paper cites Noise-free optimization in early training steps for image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Noise-free optimization in early training steps for image super-resolution

Reference 31

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Source-reported events for the cited work

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Observation fd742048-6f3c-4d27-80ad-9f9ab2a09418 · outbound

This paper cites Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation

Reference 32

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Unavailable: canonical work link unavailable.

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Observation 5c400c12-fc80-4a76-b39c-9e9fd85c2db2 · outbound

This paper cites Sed: Semantic-aware dis- criminator for image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Sed: Semantic-aware dis- criminator 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 2026-08-23T06:30:58.430688+00:00.

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Observation 51ab0be8-39ec-4eae-802d-8330d253f99f · outbound

This paper cites On Efficient Transformer-Based Image Pre-training for Low-Level Vision.

Auto-Encoded Supervision for Perceptual Image Super-Resolution On Efficient Transformer-Based Image Pre-training for Low-Level Vision

Reference 34

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Observation 43876c20-2f01-4c07-b8b8-e354b064ccc0 · outbound

This paper cites Lsdir: A large scale dataset for image restoration.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Lsdir: A large scale dataset for image restoration

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 373e89fb-3362-44aa-8916-4caaeed2f9eb · outbound

This paper cites Swinir: Image restoration us- ing swin transformer.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Swinir: Image restoration us- ing swin transformer

Reference 36

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Unavailable: canonical work link unavailable.

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Observation c42053ee-adc7-46a3-a288-5799539fa576 · outbound

This paper cites Details or artifacts: A locally discriminative learning approach to realistic im- age super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Details or artifacts: A locally discriminative learning approach to realistic im- age super-resolution

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.031192Z digest=sha256:aac933e30ee4e3c98dc6ed85732d6e6cf29e1c1854937296eaf21cad0cae30ee

Observation b0b7ee75-a6cf-4773-b053-bdda73d5bd8b · outbound

This paper cites Enhanced deep residual networks for single image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Enhanced deep residual networks for single image super-resolution

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.044648Z digest=sha256:60061872651f52767a6e0c8d0e151f51c447838ed346c0741ea142d4343d5161

Observation 4e5351a3-2f79-4f07-8d99-296901a7455b · outbound

This paper cites Enhanced deep residual networks for single image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Enhanced deep residual networks for single image super-resolution

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.055971Z digest=sha256:398eb69c823b0eac78189055d6c59c117285df56c8646e002a5bc88dcef99b06

Observation 425510e6-30c1-4a5f-b839-0e5a91e97e03 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Swin transformer: Hierarchical vision transformer using shifted windows

Reference 40

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.061473Z digest=sha256:4b2deb7a8c96bf4ab43a0771da34dfca0c4b3fca54c87696d94008e43af0084f

Observation 40a93b68-517e-41b3-80db-f22a86be6d07 · outbound

This paper cites Srflow: Learning the super-resolution space with normalizing flow.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Srflow: Learning the super-resolution space with normalizing flow

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:35.545785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.071336Z digest=sha256:8792336e96749fae1254ac8d7de26fa4808d9f2553cf0e181adf9ca411273e7b

Observation a3aa81d7-7e7c-4596-856d-c1c66fc3771f · outbound

This paper cites Structure-preserving image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Structure-preserving image super-resolution

Reference 42

Resolution
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raw_fallback, observed 2026-08-12T10:41:35.511073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.079374Z digest=sha256:e34102a1c3b9f3e580d733f957a6256288431781c55db85d2a37762dc4d89f6a

Observation e7b51c28-887c-409b-bb2c-374e6ec0a91e · outbound

This paper cites A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics.

Auto-Encoded Supervision for Perceptual Image Super-Resolution A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.087080Z digest=sha256:eb225252ffbe944c771466d31b7566f60785c916fed198183685c409da9b9f1a

Observation 6e959dd5-7558-4f28-b94f-309e970dc250 · outbound

This paper cites Sketch-based manga retrieval using manga109 dataset.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Sketch-based manga retrieval using manga109 dataset

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:35.439800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.096466Z digest=sha256:4c73c36e3dcd541e9f86d7c555d9c571df4c9280fa7b84009747effd4624c8b1

Observation 8b22313d-50d8-45be-95cd-155f69faf0a9 · outbound

This paper cites Image super- resolution with non-local sparse attention.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Image super- resolution with non-local sparse attention

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:35.407780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.103776Z digest=sha256:2a897e8be44da4ab9db793759bd064e3fea6d64a516aead40d1f6cb88b55172e

Observation aa48369e-33e0-4d4a-a850-12bbb66ac209 · outbound

This paper cites completely blind.

Auto-Encoded Supervision for Perceptual Image Super-Resolution completely blind

Reference 46

Resolution
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no resolver link, observed 2026-08-12T10:41:34.111397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.111397Z digest=sha256:22611b990f2c9f55830cb122649d003737b6880f1471bd00adc9b57b20642084

Observation 903f2899-5367-4499-9ea7-2d8c3a8c9f86 · outbound

This paper cites Single image super-resolution via a holistic attention network.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Single image super-resolution via a holistic attention network

Reference 47

Resolution
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raw_fallback, observed 2026-08-12T10:41:35.343025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.119456Z digest=sha256:3bb6503d604bf559c7e8bb2521380874b1b0a544e8018d906fbb1f013b31af3e

Observation c58df2f9-0841-464d-9812-08a94f14292b · outbound

This paper cites Content-aware local gan for photo-realistic super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Content-aware local gan for photo-realistic super-resolution

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:35.289272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.128198Z digest=sha256:d79e51bee6a97d95f82e6facd6861998c5a694ffa608ad9a650946441b48880f

Observation 33886935-e56c-4d76-9501-947caa686ab1 · outbound

This paper cites Perception-oriented single image super-resolution using op- timal objective estimation.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Perception-oriented single image super-resolution using op- timal objective estimation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:35.261244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.134852Z digest=sha256:576e332d06ca6f496d98742464aa017e540aee3babcbc885a882eba5b14b46b1

Observation c727e7bb-05bb-4965-9c62-eee8ddec0c79 · outbound

This paper cites Image super- resolution via iterative refinement.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Image super- resolution via iterative refinement

Reference 50

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.141754Z digest=sha256:35e44102a1be3b19e1c3488f1c5e86a39beb0cc9a4a527041b1e75ceedf7a68c

Observation 7dcceca3-bf12-4bf6-bdbc-78c67154e631 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 51

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source=pdf_text observed=2026-08-12T10:41:34.149646Z digest=sha256:6926a47a0667dcd594537144cc52600aba1eb6d94a49556c2073607ef8c6d394

Observation 61d669d7-c3eb-4061-b42f-f696ed82c60e · outbound

This paper cites Ex- ploring clip for assessing the look and feel of images.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Ex- ploring clip for assessing the look and feel of images

Reference 52

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.163800Z digest=sha256:5f836eb53f0a908a22aaa856368f339a0786afc3cf7b96c9b5bef20e7427b264

Observation 23f2b912-e9b5-41e7-858a-9b59cf661b6e · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Exploiting diffusion prior for real-world image super-resolution

Reference 53

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.171180Z digest=sha256:4d1965912d9be9dbea93f8e1da6e2dac8e223124a9e44eb6445ea65a7aee0be6

Observation ab0dbff6-aaa0-43a7-a28b-533398e55e29 · outbound

This paper cites Esrgan: En- hanced super-resolution generative adversarial networks.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Esrgan: En- hanced super-resolution generative adversarial networks

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:35.151934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.177331Z digest=sha256:e5bf5a621ada1b6bb8c256f2f0012450acc8ad040d09236eb814f407c191adb9

Observation 6f631537-407e-42a1-a923-6a739a227e2a · outbound

This paper cites Real-esrgan: Training real-world blind super-resolution with pure synthetic data.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Real-esrgan: Training real-world blind super-resolution with pure synthetic data

Reference 55

Resolution
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raw_fallback, observed 2026-08-12T10:41:35.114539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.185383Z digest=sha256:bb658e5d24c7c32f85e76fbc7bb4e94d55767f507094b84ad44137fe5addcf5b

Observation ff484b61-1421-42d2-99a1-d8305b1a95f9 · outbound

This paper cites Chan, Chen Change Loy, and Chao Dong.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Chan, Chen Change Loy, and Chao Dong

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:35.084381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.195857Z digest=sha256:69d337babe0576e8272731528c5b154cdc577db2e1e556f72f0cded19c082354

Observation 88b05728-7d4b-48bf-8671-f2df1366967d · outbound

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

Auto-Encoded Supervision for Perceptual Image Super-Resolution Image quality assessment: from error visibility to structural similarity

Reference 57

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.203206Z digest=sha256:cf8b8f15f61111426266ff101cfd61fc2638fb2afad54fef0a73685ae1b2d5a9

Observation 88a9d5ce-18c0-41b4-8948-0c8070615012 · outbound

This paper cites Component divide- and-conquer for real-world image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Component divide- and-conquer for real-world image super-resolution

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:34.999013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.214662Z digest=sha256:f803e3a6df065624464198797a3443a7ce609c8cc9eb8ac5c37e6c14ea798405

Observation 1c7fb7d8-ef7f-4c54-a96b-750bb00996fc · outbound

This paper cites Desra: Detect and delete the artifacts of gan-based real-world super-resolution models.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Desra: Detect and delete the artifacts of gan-based real-world super-resolution models

Reference 59

Resolution
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raw_fallback, observed 2026-08-12T10:41:34.953277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.225970Z digest=sha256:39afec02e24e5454d4e595aa0700f852a1e553e91d92bda9bffab9f23acc5eeb

Observation 2f64f07e-6c4d-4d09-a971-fac6d1b432fb · outbound

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

Auto-Encoded Supervision for Perceptual Image Super-Resolution Maniqa: Multi-dimension attention network for no-reference image quality assessment

Reference 60

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T10:41:34.237006Z digest=sha256:3a09a44579eafa79fb1bfc5d9e4dd935a053f4012f1c5ef2525f387c8c7e2b88

Observation e7438ebb-2388-46aa-8f61-b6c275fa0dea · outbound

This paper cites Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild

Reference 61

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T10:41:34.244895Z digest=sha256:bce87be252bfb1fbf5b40258f5e864dc3cebdb1971f2ad0b35ebdbf092e15638

Observation 72576f40-d3f7-4a5e-b899-e1a7e6a27577 · outbound

This paper cites On sin- gle image scale-up using sparse-representations.

Auto-Encoded Supervision for Perceptual Image Super-Resolution On sin- gle image scale-up using sparse-representations

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:34.856267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.251282Z digest=sha256:e1d48460cb6035526d0831d6686e66589580206c042ec7a9f89a6edc2e938a2b

Observation 3d7f98a3-45fa-4488-8073-048a6c4a28da · outbound

This paper cites SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution

Reference 63

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.261037Z digest=sha256:c838d3444951dc2cd68a51866025ad6290bb6cedaa990957b4f79847b4a15ed0

Observation 93ff0aaa-bf2d-4d55-bd06-b4c690c233eb · outbound

This paper cites Deep unfold- ing network for image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Deep unfold- ing network for image super-resolution

Reference 64

Resolution
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raw_fallback, observed 2026-08-12T10:41:34.824945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.270151Z digest=sha256:c68bba1e1efcab1581c591452a893e331102229e5fcab016ea54636685f8c9cb

Observation 37379fa5-fcd6-4cfb-81da-06e608ba7da5 · outbound

This paper cites Designing a practical degradation model for deep blind im- age super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Designing a practical degradation model for deep blind im- age super-resolution

Reference 65

Resolution
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raw_fallback, observed 2026-08-12T10:41:34.795176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.278156Z digest=sha256:8100a08b0a58f25ccbe5bfb01255b74e05751f4c646fdeac083c2109c47a104d

Observation 8e40e5d8-725a-40ef-8e3b-6d90416b6db7 · outbound

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

Auto-Encoded Supervision for Perceptual Image Super-Resolution The unreasonable effectiveness of deep features as a perceptual metric

Reference 66

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.284897Z digest=sha256:9b9c3ce424bd404e4a0c927d57ec7c3138ca781e321b750c6ccf70593ae029f0

Observation 57073034-8d4c-4070-912e-6f77050cb505 · outbound

This paper cites Ranksrgan: Generative adversarial networks with ranker for image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Ranksrgan: Generative adversarial networks with ranker for image super-resolution

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:34.735591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.290907Z digest=sha256:3322937a8529dd2db7c11414a06c46c9baf7fcc10aaa4d318c8722fba462fd7e

Observation a6453ca0-a3d8-4740-8b80-eca391a39f11 · outbound

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

Auto-Encoded Supervision for Perceptual Image Super-Resolution Image super-resolution using very deep residual channel attention networks

Reference 68

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no resolver link, observed 2026-08-12T10:41:34.296614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:34.296614Z digest=sha256:4c51ce87f539e9b084c52819902300883ca7f4312264f4ba8b43baef2971bfa3

Observation 54463e0e-3c90-4a37-a9bb-6caf5db4956c · outbound

This paper cites Perception- distortion balanced admm optimization for single-image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Perception- distortion balanced admm optimization for single-image super-resolution

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:34.674135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.305482Z digest=sha256:db1014708f644c4964b3c9d5667383d6ab45538859f30a8360ff8b41f120d057

Observation adaa44df-c08c-4159-bb22-1e72aec7f014 · outbound

This paper cites Cross-scale internal graph neural network for image super-resolution.

Auto-Encoded Supervision for Perceptual Image Super-Resolution Cross-scale internal graph neural network for image super-resolution

Reference 70

Resolution
malformed identifier
raw_fallback, observed 2026-08-12T10:41:34.643755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-12T10:41:34.313711Z digest=sha256:fe59240d75de63cd5f05af7f55cf2891ba540e2020dffac8aa8093b686ee375f

Pith citing papers

No inbound Pith citation observations are available.