NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results | Paper Citation Record

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Ntire 2017 challenge on single image super-resolution: Dataset and study

Reference 1

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Observation 39ce3bd1-03e9-45a4-ad7c-f0b7ce57b93a · outbound

This paper cites Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection

Reference 2

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This paper cites Activating More Pixels in Image Super-Resolution Transformer.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Activating More Pixels in Image Super-Resolution Transformer

Reference 3

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Activating more pixels in image super- resolution transformer

Reference 4

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This paper cites NTIRE 2025 challenge on image super-resolution (×4): Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on image super-resolution (×4): Methods and results

Reference 5

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This paper cites NTIRE 2025 challenge on real-world face restoration: Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on real-world face restoration: Methods and results

Reference 6

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This paper cites Nafssr: Stereo image super-resolution using nafnet.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Nafssr: Stereo image super-resolution using nafnet

Reference 7

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This paper cites NTIRE 2025 challenge on raw image restoration and super-resolution.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on raw image restoration and super-resolution

Reference 8

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Observation 0d04639a-7f4f-4b61-a013-7e82f67c8064 · outbound

This paper cites Raw image reconstruc- tion from RGB on smartphones.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Raw image reconstruc- tion from RGB on smartphones

Reference 9

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Observation 6ad7595b-d480-40a1-8a2d-e517f8644817 · outbound

This paper cites Imagenet: A large-scale hierarchical im- age database.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Imagenet: A large-scale hierarchical im- age database

Reference 10

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Observation 151a9dc4-2e3d-4bf0-8198-90c34b477545 · outbound

This paper cites NTIRE 2025 challenge on night photography rendering.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on night photography rendering

Reference 11

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Observation cfa3b747-3108-4b13-b302-5911f5834e35 · outbound

This paper cites X3d: Expanding architectures for efficient video recognition.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results X3d: Expanding architectures for efficient video recognition

Reference 12

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Observation 6f221293-b620-4050-8826-e03b3f9b7fc0 · outbound

This paper cites Slowfast networks for video recognition.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Slowfast networks for video recognition

Reference 13

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Observation feabd7e6-28f9-49dc-bfa5-e732f5d95377 · outbound

This paper cites NTIRE 2025 challenge on cross-domain few-shot object detection: Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on cross-domain few-shot object detection: Methods and results

Reference 14

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Observation f93a7e3c-7154-43a6-9a11-dce524bfaf5e · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 15

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This paper cites InternVQA: Advancing Compressed Video Quality Assessment with Distilling Large Foundation Model.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results InternVQA: Advancing Compressed Video Quality Assessment with Distilling Large Foundation Model

Reference 16

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Observation be75a2a5-af41-40f4-8e0b-d96834f87df2 · outbound

This paper cites MambaIRv2: Attentive State Space Restoration.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results MambaIRv2: Attentive State Space Restoration

Reference 17

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Observation c85cbb5d-b0f9-4ef9-bc3f-304a97dd36bf · outbound

This paper cites Mambair: A simple baseline for image restoration with state-space model.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Mambair: A simple baseline for image restoration with state-space model

Reference 18

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Observation bfad72f8-43a2-47df-821e-235b65625007 · outbound

This paper cites NTIRE 2025 challenge on text to image generation model qual- ity assessment.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on text to image generation model qual- ity assessment

Reference 19

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Observation 2409ac13-9bb2-49d9-aa08-2eda33777022 · outbound

This paper cites Deep residual learning for image recognition.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Deep residual learning for image recognition

Reference 20

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Observation 2fa68b3d-b4cb-4636-8a76-4f53484ee8a2 · outbound

This paper cites Deep residual learning for image recognition.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Deep residual learning for image recognition

Reference 21

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Observation 303d1388-d85e-439b-93dd-4e8f64ded2ac · outbound

This paper cites NTIRE 2025 challenge on video quality enhancement for video conferencing: Datasets, methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on video quality enhancement for video conferencing: Datasets, methods and results

Reference 22

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This paper cites Hiif: Hi- erarchical encoding based implicit image function for con- tinuous super-resolution.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Hiif: Hi- erarchical encoding based implicit image function for con- tinuous super-resolution

Reference 23

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Observation c9f2eec3-b340-4bbd-b0a1-a0bb7cbe933f · outbound

This paper cites C2D-ISR: Optimizing Attention-based Image Super-resolution from Continuous to Discrete Scales.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results C2D-ISR: Optimizing Attention-based Image Super-resolution from Continuous to Discrete Scales

Reference 24

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Observation 13ad66c2-8287-4627-bc33-c4b780d491c3 · outbound

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results A style-based generator architecture for generative adversarial networks

Reference 25

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Observation 8e50dd6f-a776-4a8e-baf1-c722b59e64b6 · outbound

This paper cites One millisecond face alignment with an ensemble of regression trees.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results One millisecond face alignment with an ensemble of regression trees

Reference 26

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This paper cites Accu- rate image super-resolution using very deep convolutional networks.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Accu- rate image super-resolution using very deep convolutional networks

Reference 27

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Observation 5c39f5bf-8699-487c-99d5-3ddf3a74dd73 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Adam: A Method for Stochastic Optimization

Reference 28

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This paper cites NTIRE 2025 challenge on efficient burst hdr and restoration: Datasets, methods, and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on efficient burst hdr and restoration: Datasets, methods, and results

Reference 29

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This paper cites Hst: Hierarchical swin transformer for com- pressed image super-resolution.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Hst: Hierarchical swin transformer for com- pressed image super-resolution

Reference 30

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Sed: Semantic-aware discriminator for image super-resolution

Reference 31

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Videomamba: State space model for efficient video understanding

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This paper cites A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective

Reference 33

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This paper cites Learning distortion invariant representation for im- age restoration from a causality perspective.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Learning distortion invariant representation for im- age restoration from a causality perspective

Reference 34

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This paper cites Ucip: A universal frame- work for compressed image super-resolution using dynamic prompt.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Ucip: A universal frame- work for compressed image super-resolution using dynamic prompt

Reference 35

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This paper cites Ntire 2024 challenge on short-form ugc video qual- ity assessment: Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Ntire 2024 challenge on short-form ugc video qual- ity assessment: Methods and results

Reference 36

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Observation f9e78419-85a4-4a0e-9902-bf708f41db52 · outbound

This paper cites NTIRE 2025 challenge on day and night raindrop removal for dual-focused images: Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on day and night raindrop removal for dual-focused images: Methods and results

Reference 37

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This paper cites NTIRE 2025 challenge on short-form ugc video quality assessment and enhancement: Kwaisr dataset and study.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on short-form ugc video quality assessment and enhancement: Kwaisr dataset and study

Reference 38

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This paper cites NTIRE 2025 challenge on short-form ugc video qual- ity assessment and enhancement: Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on short-form ugc video qual- ity assessment and enhancement: Methods and results

Reference 39

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This paper cites Lsdir: A large scale dataset for image restora- tion.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Lsdir: A large scale dataset for image restora- tion

Reference 40

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Observation 831a5112-c45d-43c9-aceb-82b0748e8646 · outbound

This paper cites Swinir: Image restoration using swin transformer.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Swinir: Image restoration using swin transformer

Reference 41

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This paper cites NTIRE 2025 the 2nd restore any image model (RAIM) in the wild challenge.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 the 2nd restore any image model (RAIM) in the wild challenge

Reference 42

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Observation b2467abd-3d85-42be-b8ab-43a06c2e84fc · outbound

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Enhanced deep residual networks for single image super-resolution

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.923910Z

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Enhanced deep residual networks for sin- gle image super-resolution

Reference 44

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Observation 20971399-c19f-440f-8b51-f26ecaa4637a · outbound

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Enhanced deep residual networks for single image super-resolution

Reference 45

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Observation 4f0f6f46-a9ab-4f98-b313-94d0beda36c8 · outbound

This paper cites Ada- dqa: Adaptive diverse quality-aware feature acquisition for video quality assessment.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Ada- dqa: Adaptive diverse quality-aware feature acquisition for video quality assessment

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.878615Z

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Observation a832f7ab-16a9-4c4e-a048-1350deb86212 · outbound

This paper cites NTIRE 2025 XGC quality assessment challenge: Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 XGC quality assessment challenge: Methods and results

Reference 47

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Observation c9e79a95-6d13-4bcb-b932-f6426e027381 · outbound

This paper cites NTIRE 2025 challenge on low light image enhancement: Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on low light image enhancement: Methods and results

Reference 48

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Observation 4fcdbe0c-b7e7-488c-a1cc-bcbd4ffaa8d3 · outbound

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Swin transformer: Hierarchical vision transformer using shifted windows

Reference 49

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Observation 2eef4046-f0a2-4c68-ac86-785f59e1d251 · outbound

This paper cites Swin transformer v2: Scaling up capacity and resolu- tion.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Swin transformer v2: Scaling up capacity and resolu- tion

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.828586Z

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Observation e09f835a-5698-4097-b8f5-c8f3ad79711c · outbound

This paper cites Kvq: Kwai video quality assessment for short-form videos.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Kvq: Kwai video quality assessment for short-form videos

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.815309Z

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Observation b8185507-09db-47e1-a66b-b1cfca1cd4ab · outbound

This paper cites Q-Adapt: Adapting LMM for Visual Quality Assessment with Progressive Instruction Tuning.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Q-Adapt: Adapting LMM for Visual Quality Assessment with Progressive Instruction Tuning

Reference 52

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Observation 47a4cc49-e1c7-4c1d-9f1e-dd24601595da · outbound

This paper cites Transformer for Single Image Super-Resolution.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Transformer for Single Image Super-Resolution

Reference 53

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Observation 23ad7806-da29-4a03-aaef-48ff1119bd96 · outbound

This paper cites Transformer for single image super-resolution.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Transformer for single image super-resolution

Reference 54

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Observation 347a78b2-b24f-466a-b77d-bccdbfda11fb · outbound

This paper cites Reduced- reference video quality assessment of compressed video se- quences.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Reduced- reference video quality assessment of compressed video se- quences

Reference 55

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This paper cites Bvi-aom: A new training dataset for deep video compression optimization.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Bvi-aom: A new training dataset for deep video compression optimization

Reference 56

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This paper cites Scalable diffusion mod- els with transformers.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Scalable diffusion mod- els with transformers

Reference 57

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This paper cites XPSR: cross-modal priors for diffusion-based image super-resolution.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results XPSR: cross-modal priors for diffusion-based image super-resolution

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.731862Z

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Observation bcc9ea90-b67a-42d1-832f-af5538fc1c53 · outbound

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results KVQ: Boosting Video Quality Assessment via Saliency-guided Local Perception

Reference 59

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results SAM 2: Segment Anything in Images and Videos

Reference 60

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results The tenth NTIRE 2025 efficient super-resolution challenge report

Reference 61

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results MambaCSR: Dual-Interleaved Scanning for Compressed Image Super-Resolution With SSMs

Reference 62

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on UGC video enhancement: Meth- ods and results

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.703114Z

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Observation db6691c4-e191-4953-91e9-b9a542b0cbd8 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 64

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Video quality assessment by reduced reference spatio-temporal entropic differencing

Reference 65

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Pixel-level and Semantic-level Adjustable Super-resolution: A Dual-LoRA Approach

Reference 66

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on event-based image deblurring: Methods and results

Reference 67

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results The tenth ntire 2025 image denoising challenge report

Reference 68

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This paper cites Deep learning based full-reference and no- reference quality assessment models for compressed ugc videos.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Deep learning based full-reference and no- reference quality assessment models for compressed ugc videos

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.649302Z

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Observation fc27ac00-ed8a-4869-b983-8f4e6b8421f8 · outbound

This paper cites A deep learning based no-reference quality assessment model for ugc videos.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results A deep learning based no-reference quality assessment model for ugc videos

Reference 70

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This paper cites A deep learning based no-reference quality assessment model for ugc videos.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results A deep learning based no-reference quality assessment model for ugc videos

Reference 71

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This paper cites Analysis of video quality datasets via design of minimalistic video quality models.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Analysis of video quality datasets via design of minimalistic video quality models

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.615540Z

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This paper cites Enhancing blind video quality assessment with rich quality-aware features.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Enhancing blind video quality assessment with rich quality-aware features

Reference 73

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This paper cites An empirical study for efficient video quality assessment.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results An empirical study for efficient video quality assessment

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.603115Z

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This paper cites Frank: a ranking method with fidelity loss.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Frank: a ranking method with fidelity loss

Reference 75

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Observation c419c973-d1b1-4539-9239-267fcdb35930 · outbound

This paper cites Ugc-vqa: Benchmarking blind video quality assessment for user generated content.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Ugc-vqa: Benchmarking blind video quality assessment for user generated content

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.574700Z

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Observation 362cd461-a7ff-48f2-9fa8-ba1e10adc7ec · outbound

This paper cites Maxim: Multi-axis mlp for image processing.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Maxim: Multi-axis mlp for image processing

Reference 77

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 image shadow removal challenge report

Reference 78

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 ambi- ent lighting normalization challenge

Reference 79

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Unresolved cited work

Reference 80

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This paper cites Lit: Delving into a simplified linear diffusion transformer for image generation.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Lit: Delving into a simplified linear diffusion transformer for image generation

Reference 81

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This paper cites Recovering realistic texture in image super-resolution by deep spatial feature transform.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Recovering realistic texture in image super-resolution by deep spatial feature transform

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.522807Z

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Real-esrgan: Training real-world blind super-resolution with pure synthetic data

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.509482Z

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Sinsr: diffusion-based image super- resolution in a single step

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.496583Z

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This paper cites Enhanced semantic extraction and guid- ance for ugc image super resolution.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Enhanced semantic extraction and guid- ance for ugc image super resolution

Reference 85

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Observation 118cc4d8-69b9-482b-82ad-7b20fa9569e2 · outbound

This paper cites NTIRE 2025 challenge on light field image super-resolution: Methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on light field image super-resolution: Methods and results

Reference 86

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This paper cites Fast- vqa: Efficient end-to-end video quality assessment with fragment sampling.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Fast- vqa: Efficient end-to-end video quality assessment with fragment sampling

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.460615Z

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This paper cites Exploring video quality assessment on user gener- ated contents from aesthetic and technical perspectives.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Exploring video quality assessment on user gener- ated contents from aesthetic and technical perspectives

Reference 88

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Observation e01cdc38-268c-4ccd-89e2-2a4678bd9540 · outbound

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

Reference 89

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Q-instruct: Improving low-level visual abilities for multi-modality foundation models

Reference 90

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NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Seesr: Towards semantics- aware real-world image super-resolution

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.430601Z

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Observation 563575e1-9d8e-41a1-8a57-5fc94bd636c2 · outbound

This paper cites QPT-V2: masked image mod- eling advances visual scoring.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results QPT-V2: masked image mod- eling advances visual scoring

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.417813Z

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Observation 29748a5d-fc8f-40ec-ba58-f4aa21d929f2 · outbound

This paper cites NTIRE 2025 challenge on single image reflection removal in the wild: Datasets, methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results NTIRE 2025 challenge on single image reflection removal in the wild: Datasets, methods and results

Reference 93

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This paper cites Aim 2022 challenge on super-resolution of compressed image and video: Dataset, methods and results.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Aim 2022 challenge on super-resolution of compressed image and video: Dataset, methods and results

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.395957Z

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Observation c79c56e8-b4bc-417c-bcc2-488d04d5f3ff · outbound

This paper cites Wider face: A face detection benchmark.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Wider face: A face detection benchmark

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.381679Z

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Observation 74908317-4d94-4ce9-a648-67171f6d97fd · outbound

This paper cites Patch-vq:’patching up’the video qual- ity problem.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Patch-vq:’patching up’the video qual- ity problem

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.368050Z

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Observation dd385781-6f02-4e49-ba87-46154c9f002f · outbound

This paper cites Teaching large language models to regress accu- rate image quality scores using score distribution.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Teaching large language models to regress accu- rate image quality scores using score distribution

Reference 97

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Observation a74b0297-f09f-4ec7-9e7a-8c3939734afd · outbound

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

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.354169Z

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Observation 5ab576e5-45f8-48b2-952e-0a1818196bb8 · outbound

This paper cites Sf-iqa: Quality and similarity integration for ai generated image quality assessment.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Sf-iqa: Quality and similarity integration for ai generated image quality assessment

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:16:39.341983Z

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Observation e8c7d5a5-7045-4f7d-9c4a-120e21fbc9f8 · outbound

This paper cites Video Quality Assessment Based on Swin TransformerV2 and Coarse to Fine Strategy.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results Video Quality Assessment Based on Swin TransformerV2 and Coarse to Fine Strategy

Reference 100

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