PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution | Paper Citation Record

Observation 17124fb4-5307-4e4a-a0bf-1aea41593b8d · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Ntire 2017 chal- lenge on single image super-resolution: Dataset and study

Reference 1

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Observation 2a8afa5f-79a2-4b79-8b10-78271932c434 · outbound

This paper cites Cross aggregation transformer for image restoration.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Cross aggregation transformer for image restoration

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.460619Z

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Observation 19996bf5-bf93-4563-87e8-1135c645280a · outbound

This paper cites Cross aggregation transformer for image restoration.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Cross aggregation transformer for image restoration

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.450215Z

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Observation 85ef0c2b-1b15-4e92-8aea-02120bf0bd86 · outbound

This paper cites Dual aggregation transformer for image super-resolution.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Dual aggregation transformer for image super-resolution

Reference 4

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Observation 1c905ec1-c54d-4143-bae0-df71c09d3c49 · outbound

This paper cites Image quality assessment: Unifying struc- ture and texture similarity.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Image quality assessment: Unifying struc- ture and texture similarity

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.429750Z

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Observation 0ef45c12-2def-479d-9b44-cc02bf7ef5b2 · outbound

This paper cites Towards accurate post-training quantization for vision trans- former.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Towards accurate post-training quantization for vision trans- former

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.419717Z

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Observation 1a6cd110-2ebd-477f-a03a-28a335cb248c · outbound

This paper cites Image super-resolution using deep convo- lutional networks.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Image super-resolution using deep convo- lutional networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.409369Z

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Observation 6001ce9d-148a-4d3b-9a63-4f5dea20ff7c · outbound

This paper cites Learned step size quantization.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Learned step size quantization

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.399820Z

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Observation b1fb498a-8e3d-4562-89f5-9c96b39e877e · outbound

This paper cites EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models

Reference 9

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Observation 43261d5f-5bb1-47fc-9742-afb6cfe1e496 · outbound

This paper cites Ptqd: Accurate post- training quantization for diffusion models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Ptqd: Accurate post- training quantization for diffusion models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.390113Z

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Observation cb4ca918-4f33-4288-ae9f-264197433563 · outbound

This paper cites Accurate post training quantiza- tion with small calibration sets.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Accurate post training quantiza- tion with small calibration sets

Reference 11

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Observation 0387e517-e230-439d-9420-55261c49e98b · outbound

This paper cites Quantization and train- ing of neural networks for efficient integer-arithmetic- only inference.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Quantization and train- ing of neural networks for efficient integer-arithmetic- only inference

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.370611Z

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Observation 0809a4bc-486c-4015-8d9d-721827011230 · outbound

This paper cites Real-world super- resolution via kernel estimation and noise injection.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Real-world super- resolution via kernel estimation and noise injection

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.360590Z

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Observation f730f3a0-7975-461f-92fb-5d9d4c4b1223 · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Musiq: Multi-scale image quality transformer

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.350389Z

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Observation 91d4eea9-fe02-43b5-b1a3-70988bc19110 · outbound

This paper cites Ac- curate image super-resolution using very deep convo- lutional networks.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Ac- curate image super-resolution using very deep convo- lutional networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.340249Z

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Observation 67e8cccd-93c0-41e8-a835-bda845562f58 · outbound

This paper cites Low-bit quantization of neural networks for efficient inference.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Low-bit quantization of neural networks for efficient inference

Reference 16

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Observation 51fc6812-c983-4e22-965d-23b0960b2885 · outbound

This paper cites Unleashing the Power of One-Step Diffusion based Image Super-Resolution via a Large-Scale Diffusion Discriminator.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Unleashing the Power of One-Step Diffusion based Image Super-Resolution via a Large-Scale Diffusion Discriminator

Reference 17

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Observation 44dde6e3-7c00-4142-804d-2ea442b2cc2f · outbound

This paper cites Q-diffusion: Quantizing diffusion models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Q-diffusion: Quantizing diffusion models

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.319690Z

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Observation b659237e-d9db-443a-a87f-7ce19a20df2e · outbound

This paper cites BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T12:34:42.778111Z

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Observation b042eb6a-43c3-4428-9e53-6f5ba517fb55 · outbound

This paper cites Q-dm: An efficient low-bit quan- tized diffusion model.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Q-dm: An efficient low-bit quan- tized diffusion model

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.309746Z

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Observation 79e52d67-6ece-4c38-a160-8ac93b1e2967 · outbound

This paper cites Swinir: Image restoration using swin transformer.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Swinir: Image restoration using swin transformer

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.300003Z

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Observation 1e2bdc18-a19c-4b2e-95ac-ddc72e837e13 · outbound

This paper cites Awq: Activation-aware weight quantization for on-device llm compression and acceleration.Proceedings of Ma- chine Learning and Systems, 2024.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Awq: Activation-aware weight quantization for on-device llm compression and acceleration.Proceedings of Ma- chine Learning and Systems, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.290237Z

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Observation d1dadc90-59c3-4214-8d0b-8e74f730f736 · outbound

This paper cites Diffbir: Towards blind image restoration with generative diffusion prior.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Diffbir: Towards blind image restoration with generative diffusion prior

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.280211Z

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Observation a1ee1b6a-13ae-4920-b8c3-684c5e24ea76 · outbound

This paper cites Nonuniform-to-uniform quantization: Towards accurate quantization via gen- eralized straight-through estimation.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Nonuniform-to-uniform quantization: Towards accurate quantization via gen- eralized straight-through estimation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.269365Z

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Observation 9481735a-40fc-4f12-803b-097a98035315 · outbound

This paper cites SmoothQuant+: Accurate and Efficient 4-bit Post-Training WeightQuantization for LLM.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution SmoothQuant+: Accurate and Efficient 4-bit Post-Training WeightQuantization for LLM

Reference 25

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Observation 3533fd46-e859-473f-8eb0-435b3996dc6e · outbound

This paper cites Quantsr: ac- curate low-bit quantization for efficient image super- resolution.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Quantsr: ac- curate low-bit quantization for efficient image super- resolution

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.258769Z

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Observation 7197b5f5-79a8-4a38-a7bc-0fb29ead49e4 · outbound

This paper cites High- 9 resolution image synthesis with latent diffusion mod- els.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution High- 9 resolution image synthesis with latent diffusion mod- els

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.248353Z

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Observation 327e536d-48ee-4265-9c91-3e489948a2dd · outbound

This paper cites Post-training quantization on diffusion models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Post-training quantization on diffusion models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.237020Z

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Observation 6f0ee9bd-13e0-4ef8-80d2-7e208180b8a3 · outbound

This paper cites Omniquant: Omnidi- rectionally calibrated quantization for large language models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Omniquant: Omnidi- rectionally calibrated quantization for large language models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.226298Z

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Observation e04ef787-c852-4f4c-b2f3-9daa4fdbaa9f · outbound

This paper cites Temporal dynamic quanti- zation for diffusion models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Temporal dynamic quanti- zation for diffusion models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.215782Z

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Observation fb0daccc-8a99-4d7e-970c-0eb9d264034a · outbound

This paper cites Denoising diffusion implicit models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Denoising diffusion implicit models

Reference 31

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Observation 74c742d1-eed6-49eb-9616-b7af13b0d22d · outbound

This paper cites Consistency models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Consistency models

Reference 32

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Observation ad3fae1d-f687-406a-bcb9-48f7151f3a49 · outbound

This paper cites Towards accurate post- training quantization for diffusion models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Towards accurate post- training quantization for diffusion models

Reference 33

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Observation fed9aa07-2c05-4200-b85f-97b2b78f8592 · outbound

This paper cites QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning

Reference 34

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Observation d721407f-733b-4c20-8e3a-8d4a9087c368 · outbound

This paper cites Exploring clip for assessing the look and feel of im- ages.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Exploring clip for assessing the look and feel of im- ages

Reference 35

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Observation 88b53d34-79f6-490d-abb2-c96b3d9fd3ca · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Exploiting diffusion prior for real-world image super-resolution

Reference 36

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Observation 102b345d-31c7-4b5d-98cc-744ea5630faf · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Real-esrgan: Training real-world blind super- resolution with pure synthetic data

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.155616Z

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Observation e8921aeb-cdf2-4bdd-9919-c92eb2caf3a1 · outbound

This paper cites Sinsr: diffusion- based image super-resolution in a single step.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Sinsr: diffusion- based image super-resolution in a single step

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.145210Z

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Observation 08ad086e-65c8-45db-9429-9a54d4701865 · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Image quality assessment: from error visibility to structural similarity

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T12:34:42.847029Z

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Observation 5b17ac20-3f90-44ca-8b13-f4a4d73c8dcc · outbound

This paper cites Prolific- dreamer: High-fidelity and diverse text-to-3d genera- tion with variational score distillation.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Prolific- dreamer: High-fidelity and diverse text-to-3d genera- tion with variational score distillation

Reference 40

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Observation 5b07e530-d412-41fe-bcd4-057bfcb9f156 · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Compo- nent divide-and-conquer for real-world image super- resolution

Reference 41

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Observation f142724e-a91c-4d8b-ae41-1d133d5f0ed7 · outbound

This paper cites One-step effective diffusion network for real- world image super-resolution.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution One-step effective diffusion network for real- world image super-resolution

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.107702Z

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Observation 34cd5c0d-a4af-4104-84e5-c925e092cb89 · outbound

This paper cites Seesr: Towards semantics-aware real-world image super-resolution.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Seesr: Towards semantics-aware real-world image super-resolution

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.097806Z

Source-reported events for the cited work

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Observation 1252301c-6003-4679-98d0-a1ab71768aec · outbound

This paper cites Qa-lora: Quantization-aware low-rank adaptation of large language models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Qa-lora: Quantization-aware low-rank adaptation of large language models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.088082Z

Source-reported events for the cited work

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Observation 66c0e17b-8583-43bd-a9b3-96dcedb0cbe9 · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Maniqa: Multi-dimension attention network for no-reference image quality assessment

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.077204Z

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Observation 1f5d59b3-2b80-46bd-b118-8a4e291a02a8 · outbound

This paper cites Zero- quant: Efficient and affordable post-training quantiza- tion for large-scale transformers.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Zero- quant: Efficient and affordable post-training quantiza- tion for large-scale transformers

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.066179Z

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Observation 98c5ecf6-8703-4913-ac37-f9618eb7618d · outbound

This paper cites One-step diffusion with distribution matching distillation.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution One-step diffusion with distribution matching distillation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.055759Z

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Observation e84d3d37-7657-4f94-92e8-15deeef999f1 · outbound

This paper cites Ptq4vit: Post-training quantization framework for vision transformers with twin uniform quantization.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Ptq4vit: Post-training quantization framework for vision transformers with twin uniform quantization

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.045137Z

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Observation 5bfe1afe-ac9d-474a-af65-16f4629a98d1 · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Designing a practical degradation model for deep blind image super-resolution

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.034044Z

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Observation 95d00a6a-dd97-4c49-a48d-bd714388ae39 · outbound

This paper cites an unresolved cited work.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:34:43.022548Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 347282b9-0c7b-4c23-95b2-d4ccf143c64a · outbound

This paper cites The unreasonable ef- fectiveness of deep features as a perceptual metric.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution The unreasonable ef- fectiveness of deep features as a perceptual metric

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.012167Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 827aab33-cf35-4c78-8f14-19edcf01882f · outbound

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

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Image super-resolution using very deep residual channel attention networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:43.001097Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 35c05c0b-1253-4322-a37e-13d5ac414f95 · outbound

This paper cites Residual dense network for image super- resolution.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Residual dense network for image super- resolution

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:42.989520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 34bed5a2-9571-48ac-9550-a15896c7dd1e · outbound

This paper cites Unipc: A unified predictor-corrector framework for fast sampling of diffusion models.

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution Unipc: A unified predictor-corrector framework for fast sampling of diffusion models

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:34:42.977629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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