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Paper Citation Record · LEDGER

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results

As of 8 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2505.18988.

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

pith.paper-citation-record.v1
2505.18988 v1

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measured 48 of 48 reference resolution

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measured 0 of 0 inbound itemization

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Outbound references

Observation 7be4847d-5d46-4e1b-b0ee-3335f11a3330 · outbound

This paper cites Rank analysis of incomplete block designs: I.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Rank analysis of incomplete block designs: I

Reference 1

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Observation 5019f4b4-1634-4aea-a5b0-b60313de3f31 · outbound

This paper cites Learning photographic global tonal adjustment with a database of input / output image pairs.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Learning photographic global tonal adjustment with a database of input / output image pairs

Reference 2

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Observation 714561cc-7f0c-4d28-ba12-d635b7c2424b · outbound

This paper cites Basicvsr++: Improving video super- resolution with enhanced propagation and alignment.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Basicvsr++: Improving video super- resolution with enhanced propagation and alignment

Reference 3

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Observation 2b541d7e-e7f7-4149-b8e0-ff55c7b64869 · outbound

This paper cites Deep photo enhancer: Unpaired learning for image enhancement from photographs with gans.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Deep photo enhancer: Unpaired learning for image enhancement from photographs with gans

Reference 4

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Observation 3311b64c-9c6d-4212-812b-001bf6c65800 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on image super-resolution (×4): Methods and results

Reference 5

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Observation 8e3c62a9-780c-4a96-a50b-ac0be21e9f11 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on real-world face restoration: Methods and results

Reference 6

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Observation eef88737-0869-4bbc-8058-aa0e5adc8330 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on raw image restoration and super-resolution

Reference 7

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Observation 5c1401b8-f8aa-4d80-a6a9-e280281105be · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Raw image reconstruc- tion from RGB on smartphones

Reference 8

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Observation f689894f-30ef-405b-8faa-7965a7a7d9fa · outbound

This paper cites Aesthetic- driven image enhancement by adversarial learning.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Aesthetic- driven image enhancement by adversarial learning

Reference 9

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Source-reported events for the cited work

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Observation 80ca0234-393d-457e-b30b-36d669892532 · outbound

This paper cites NTIRE 2025 challenge on night photography rendering.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on night photography rendering

Reference 10

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Observation c014ece7-23ab-4296-a7a0-8d94a7186ecc · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on cross-domain few-shot object detection: Methods and results

Reference 11

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Observation 77e2aa12-1248-441e-bb3d-5a4973f269d4 · outbound

This paper cites NTIRE 2025 challenge on text to image generation model quality assess- ment.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on text to image generation model quality assess- ment

Reference 12

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Observation 22e6fad4-4f77-4cd1-a7dc-763d9da9214d · outbound

This paper cites Look ma, no markers: holistic performance capture without the hassle.ACM Transactions on Graphics (TOG), 43(6):1–12, 2024.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Look ma, no markers: holistic performance capture without the hassle.ACM Transactions on Graphics (TOG), 43(6):1–12, 2024

Reference 13

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Observation 7f34eb25-1e0f-4a53-abd6-65b774c11039 · outbound

This paper cites Dslr-quality photos on mobile devices with deep convolutional networks.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Dslr-quality photos on mobile devices with deep convolutional networks

Reference 14

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Observation a581eaa4-90d7-4db4-a93e-8fe1fc1c4da5 · outbound

This paper cites Siamese neural networks for one-shot image recognition.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Siamese neural networks for one-shot image recognition

Reference 15

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Source-reported events for the cited work

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Observation 7c24de30-f2be-458f-8064-99a302aae20f · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on efficient burst hdr and restoration: Datasets, methods, and results

Reference 16

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Observation bfd854a1-c1fa-40dd-a362-eeb1adc99aec · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on day and night raindrop removal for dual-focused images: Methods and results

Reference 17

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Observation 2b9967d2-4698-43db-bb3d-017edd14fa95 · outbound

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

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: Kwaisr dataset and study

Reference 18

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Observation e17f9f03-fcad-4a47-a2b0-29ca98ca689a · outbound

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

Reference 19

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Observation bdb09838-fd4b-42e5-b3ef-d639ee668e18 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 the 2nd restore any image model (RAIM) in the wild challenge

Reference 20

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Observation cd5e7b6a-bc3e-4353-9937-5cb2f6f96655 · outbound

This paper cites Un- supervised flow-aligned sequence-to-sequence learning for video restoration.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Un- supervised flow-aligned sequence-to-sequence learning for video restoration

Reference 21

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Observation 3dba4840-b85c-4b72-9642-6b265d145aca · outbound

This paper cites Video super-resolution based on deep learning: a compre- hensive survey.Artificial Intelligence Review, 55(8):5981– 6035, 2022.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Video super-resolution based on deep learning: a compre- hensive survey.Artificial Intelligence Review, 55(8):5981– 6035, 2022

Reference 22

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Observation 4da0f140-bb05-43b2-b758-e93549f898c1 · outbound

This paper cites NTIRE 2025 XGC quality assessment chal- lenge: Methods and results.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 XGC quality assessment chal- lenge: Methods and results

Reference 23

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Observation 02826cf2-3f9c-4b12-9e5c-958fdfacdd73 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on low light image enhancement: Methods and results

Reference 24

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Observation c10b970d-9395-403c-82fa-e5b4a3b8dea3 · outbound

This paper cites Es- timating generalized gaussian blur kernels for out-of-focus image deblurring.IEEE Transactions on circuits and sys- tems for video technology, 31(3):829–843, 2020.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Es- timating generalized gaussian blur kernels for out-of-focus image deblurring.IEEE Transactions on circuits and sys- tems for video technology, 31(3):829–843, 2020

Reference 25

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Observation 7ec10c89-3694-42e3-b47d-260f81311168 · outbound

This paper cites A crowdsourcing approach to video quality assessment.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results A crowdsourcing approach to video quality assessment

Reference 26

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Observation eb633e5c-6cac-46af-aafe-636671c23c36 · outbound

This paper cites Optical flow estima- tion using a spatial pyramid network.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Optical flow estima- tion using a spatial pyramid network

Reference 27

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Observation b40b0b58-069d-45b6-8181-1b05a8225e29 · outbound

This paper cites The tenth NTIRE 2025 efficient super- resolution challenge report.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results The tenth NTIRE 2025 efficient super- resolution challenge report

Reference 28

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Observation 8fd46974-1d0a-4359-9b1e-98d9657f4343 · outbound

This paper cites NTIRE 2025 challenge on UGC video enhancement: Meth- ods and results.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on UGC video enhancement: Meth- ods and results

Reference 29

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Observation c097b10e-1a56-4a56-ae71-fc2469d7a7f3 · outbound

This paper cites NTIRE 2025 challenge on event-based image deblurring: Methods and results.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on event-based image deblurring: Methods and results

Reference 30

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Observation 186584d7-f49b-4952-930a-2fa8eb6b9ab9 · outbound

This paper cites The tenth ntire 2025 image denoising challenge report.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results The tenth ntire 2025 image denoising challenge report

Reference 31

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Observation 1f397038-ab2f-48d1-95e6-6c8c886eb36f · outbound

This paper cites NTIRE 2025 image shadow removal challenge report.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 image shadow removal challenge report

Reference 32

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Observation 3593958d-1bec-4a0a-80aa-76b98c679bfc · outbound

This paper cites NTIRE 2025 ambi- ent lighting normalization challenge.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 ambi- ent lighting normalization challenge

Reference 33

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Observation 1ef34615-662d-41f7-8945-fa820a1fe2bf · outbound

This paper cites Q-cidnet: Perceptual quality aware color and intensity decoupling network for video quality enhancement.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Q-cidnet: Perceptual quality aware color and intensity decoupling network for video quality enhancement

Reference 34

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Source-reported events for the cited work

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

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Observation 314e3ddd-3d86-4ddb-8c51-e28bad104b46 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Ex- ploring clip for assessing the look and feel of images

Reference 35

Resolution
verified fuzzy
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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:25:59.313569Z digest=sha256:0b3cd3ffcb9826eaacd25bf953fdfe36b07a65573cab11bb315b55c9fadf4f75

Observation 9d0d59f5-92ac-411d-a116-4483f35e768d · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Real-esrgan: Training real-world blind super-resolution with pure synthetic data

Reference 36

Resolution
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no resolver link, observed 2026-08-07T14:25:59.424000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:25:59.424000Z digest=sha256:44c5d91fcf5977ebe59bc904486d2477ae4110f40846945ff630fa8e154b2664

Observation 1afe01da-ed59-4d1f-a83c-ffee270f4034 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on light field image super-resolution: Methods and results

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:25:59.525273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:25:59.525273Z digest=sha256:4b86b1d0b0a80863d7e286f687354f0cdeefb3f04d0f37c55ce1ca7c5e2e508e

Observation c624bd6b-5cbb-4a7d-b57e-4e6b153b475b · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Exploring video quality assessment on user gener- ated contents from aesthetic and technical perspectives

Reference 38

Resolution
verified fuzzy
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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:25:59.581340Z digest=sha256:b8a341d5ea99b34b5f39be09afee378d19b2697ee944ee2c6828dcba92305db7

Observation 25ff019a-596e-46af-adcc-a5628b1ef583 · outbound

This paper cites HVI: A New Color Space for Low-light Image Enhancement.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results HVI: A New Color Space for Low-light Image Enhancement

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:25:59.602765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:25:59.602765Z digest=sha256:104963840d89e37edc1d4e341d0098c9104d6e82c8e71e1b8a5c7696b191c21b

Observation d5d42738-ed59-423c-aee2-3734396900a1 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on single image reflection removal in the wild: Datasets, methods and results

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:25:59.641338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:25:59.641338Z digest=sha256:ef17c969bc1b6f6a8742aab2857423d061703501aaa16fca6bba3c9ad6798ace

Observation d0df9a5d-b961-43bb-a376-dc9b593f6a07 · outbound

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

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results AIM 2022 challenge on super-resolution of compressed image and video: Dataset, methods and results

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:26:01.561771Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:25:59.693634Z digest=sha256:a1a98589c8670ad3297f8c48cdf6200d85a653ef5f817c231d917aeae8617922

Observation 09825dd7-44fd-4aea-adfb-c8b2836b491f · outbound

This paper cites Taming lookup tables for efficient image retouching.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Taming lookup tables for efficient image retouching

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:26:01.236293Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:25:59.777073Z digest=sha256:aa10fe6dfd8087da381353c0e82ab37a3cf1004f890c15d59e330cfc17da9811

Observation 8b0a2f4c-5222-4eb2-8a2c-323b55e5d670 · outbound

This paper cites NTIRE 2025 challenge on hr depth from images of specular and transparent surfaces.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results NTIRE 2025 challenge on hr depth from images of specular and transparent surfaces

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T14:25:59.856752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:25:59.856752Z digest=sha256:cfb4dd6994cd03185e64bfbefe7096c9791a530e3d364d64fd7c1c3689606584

Observation 79085752-cec1-49ee-a3d1-71d68c7d080a · outbound

This paper cites an unresolved cited work.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:26:01.039085Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:25:59.894389Z digest=sha256:cc97deaef5d7f849ef8aed4d803dc3ad5c9a9c6315f708f5ac8c0363dd8601de

Observation f36793b3-97f0-49f7-9c15-fe940c213e67 · outbound

This paper cites Region-aware portrait retouching with sparse interactive guidance.IEEE Transactions on Multimedia, 26:127–140,.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Region-aware portrait retouching with sparse interactive guidance.IEEE Transactions on Multimedia, 26:127–140,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:26:00.861158Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:25:59.941578Z digest=sha256:8955270183c69ea01e7cd62f0a2e987a98b1df729509ed95d056bd3dfba24382

Observation 1ec91985-4d2a-4447-ab6f-b3a3512911c3 · outbound

This paper cites Clut-net: Learning adaptively compressed representations of 3dluts for lightweight image enhancement.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Clut-net: Learning adaptively compressed representations of 3dluts for lightweight image enhancement

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:26:00.736995Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:26:00.033326Z digest=sha256:d1eed0c711ed1d1f109c5df3d82378c03996876d714452a5510c64be792400e4

Observation 83393421-ec0a-4ec2-8787-ceaff592ea3c · outbound

This paper cites Multiple cycle-in-cycle generative adversar- ial networks for unsupervised image super-resolution.TIP, 29:1101–1112, 2020.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Multiple cycle-in-cycle generative adversar- ial networks for unsupervised image super-resolution.TIP, 29:1101–1112, 2020

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:26:00.562171Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:26:00.145967Z digest=sha256:cc37499f75c0ce808f31a2ec39fe98cdb7856ac8650aefa8e0c2f6725c6ffa23

Observation 582c8081-2cae-4190-8b06-3dc443d7ef09 · outbound

This paper cites Deep single-image portrait relighting.

NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results Deep single-image portrait relighting

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:26:00.396966Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:26:00.172246Z digest=sha256:152f4075ed9870df02045ded79ad296aba40c610e367b256fef261e03a1e1234

Pith citing papers

No inbound Pith citation observations are available.