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Paper Citation Record · LEDGER

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation

As of 9 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2507.15709.

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

pith.paper-citation-record.v1
2507.15709 v2

Coverage vector

measured 67 of 67 reference resolution

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measured 67 of 67 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

67 of 67 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aeff3275-bc61-4bff-9f00-5311791fc8ff · outbound

This paper cites Arniqa: Learning distortion mani- fold for image quality assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Arniqa: Learning distortion mani- fold for image quality assessment

Reference 1

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Observation 04862b7f-f8bc-4c93-a900-4ac3fe3f9c2b · outbound

This paper cites A fast approach for no- reference image sharpness assessment based on maximum local variation.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation A fast approach for no- reference image sharpness assessment based on maximum local variation

Reference 2

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Observation a2757005-d808-453f-a770-ff70b15db843 · outbound

This paper cites Deep neural net- works for no-reference and full-reference image quality as- sessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Deep neural net- works for no-reference and full-reference image quality as- sessment

Reference 3

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Observation 2584eb19-2379-4360-beae-89ead8fbb5e7 · outbound

This paper cites Generalizable Video Quality Assessment via Weak-to-Strong Learning.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Generalizable Video Quality Assessment via Weak-to-Strong Learning

Reference 4

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Source-reported events for the cited work

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Observation ce0c56af-945e-47fb-9021-dd4731924174 · outbound

This paper cites Attention-guided neural networks for full-reference and no- reference audio-visual quality assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Attention-guided neural networks for full-reference and no- reference audio-visual quality assessment

Reference 5

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Observation 13e43b0e-11d7-4144-a940-7bd6e6e57ace · outbound

This paper cites AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment

Reference 6

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Observation 5df396e3-902d-4a27-a36e-618d60a77f4f · outbound

This paper cites An image quality assessment dataset for portraits.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation An image quality assessment dataset for portraits

Reference 7

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Source-reported events for the cited work

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Observation 01fdc216-9530-41d3-88e4-57065d1cb31d · outbound

This paper cites Topiq: A top-down approach from semantics to distortions for image quality assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Topiq: A top-down approach from semantics to distortions for image quality assessment

Reference 8

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Source-reported events for the cited work

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Observation 8bc1f2f1-a067-44d6-ab16-993a607d5237 · outbound

This paper cites Dsl-fiqa: As- sessing facial image quality via dual-set degradation learn- ing and landmark-guided transformer.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Dsl-fiqa: As- sessing facial image quality via dual-set degradation learn- ing and landmark-guided transformer

Reference 9

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Source-reported events for the cited work

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Observation ef3ff400-c691-4949-baa1-4ca7ff666f75 · outbound

This paper cites Vquala 2025 chal- lenge on genai-bench aigc video quality assessment: Meth- ods and results.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Vquala 2025 chal- lenge on genai-bench aigc video quality assessment: Meth- ods and results

Reference 10

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Observation 4f2c58f3-c431-48d6-b35b-e508b1c286d8 · outbound

This paper cites A no-reference objective image sharpness metric based on the notion of just noticeable blur (jnb).

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation A no-reference objective image sharpness metric based on the notion of just noticeable blur (jnb)

Reference 11

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Source-reported events for the cited work

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Observation 632722d1-1bf0-491c-bd6c-371550dd3b8a · outbound

This paper cites Born again neural net- works.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Born again neural net- works

Reference 12

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Observation 5108c18d-6417-48b4-b8a6-59db0e500c70 · outbound

This paper cites Lmm-vqa: Advancing video quality assessment with large multimodal models.IEEE Transactions on Circuits and Systems for Video Technology, 2025.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Lmm-vqa: Advancing video quality assessment with large multimodal models.IEEE Transactions on Circuits and Systems for Video Technology, 2025

Reference 13

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Observation 58e63c1e-71ab-4d61-be19-2a6d19e51ada · outbound

This paper cites Faceqnet: Quality assessment for face recognition based on deep learning.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Faceqnet: Quality assessment for face recognition based on deep learning

Reference 14

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Observation 37ea31b2-0831-4f4d-b996-c171ba633e84 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Distilling the Knowledge in a Neural Network

Reference 15

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Observation 3037ad50-660a-407b-97c0-3ef663b1e8d1 · outbound

This paper cites Vquala 2025 doc- ument image quality assessment challenge.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Vquala 2025 doc- ument image quality assessment challenge

Reference 16

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Observation d00f219a-1d77-4753-b5ad-abb71b552800 · outbound

This paper cites Convolu- tional neural networks for no-reference image quality assess- ment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Convolu- tional neural networks for no-reference image quality assess- ment

Reference 17

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Observation 3169d004-b109-473f-af5c-a017d91829d3 · outbound

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

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Musiq: Multi-scale image quality transformer

Reference 18

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Source-reported events for the cited work

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Observation 2fae1ce2-16a9-4396-adbc-c3e227bca5a3 · outbound

This paper cites Vquala 2025 challenge on engagement prediction for short videos: Methods and results.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Vquala 2025 challenge on engagement prediction for short videos: Methods and results

Reference 19

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Observation cfa25032-0bd5-4003-911c-09708b0dd3d1 · outbound

This paper cites Vquala 2025 challenge on image super-resolution generated content qual- ity assessment: Methods and results.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Vquala 2025 challenge on image super-resolution generated content qual- ity assessment: Methods and results

Reference 20

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Observation c4bf723c-b1ec-4d81-a73a-ac9f423efd43 · outbound

This paper cites AGHI-QA: A Subjective-Aligned Dataset and Metric for AI-Generated Human Images.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation AGHI-QA: A Subjective-Aligned Dataset and Metric for AI-Generated Human Images

Reference 21

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Observation ceeb3fa2-d187-40b2-8338-776b88beb775 · outbound

This paper cites Assessing face image quality: A large-scale database and a transformer method.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Assessing face image quality: A large-scale database and a transformer method

Reference 22

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Observation 48a12e14-0365-49d4-8e68-caad9edb9bf5 · outbound

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

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Swin transformer: Hierarchical vision transformer using shifted windows

Reference 23

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Observation 7139c027-37c8-4b90-8f71-b687ff557642 · outbound

This paper cites Bh-vqa: blind high frame rate video quality assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Bh-vqa: blind high frame rate video quality assessment

Reference 24

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Source-reported events for the cited work

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Observation 572f399e-c094-4680-9a42-95e2193527a1 · outbound

This paper cites Vquala 2025 challenge on face image quality assessment: Methods and results.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Vquala 2025 challenge on face image quality assessment: Methods and results

Reference 25

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Observation 650c1046-24c3-4aa1-968e-6b24ed674ba1 · outbound

This paper cites Edgenext: efficiently amalgamated cnn-transformer architecture for mobile vision applications.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Edgenext: efficiently amalgamated cnn-transformer architecture for mobile vision applications

Reference 26

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Observation ec205cf4-c4d4-4c71-860b-7820e321f2f5 · outbound

This paper cites Image quality assessment us- ing contrastive learning.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Image quality assessment us- ing contrastive learning

Reference 27

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Source-reported events for the cited work

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Observation 48b3afa2-3039-4d51-bcf7-d5b632e97a20 · outbound

This paper cites No-reference image quality assessment in the spa- tial domain.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation No-reference image quality assessment in the spa- tial domain

Reference 28

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Observation aa2d7293-c0b8-4bba-b8aa-12a86f74e9f3 · outbound

This paper cites completely blind.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation completely blind

Reference 29

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Observation 4ba447a3-b3ec-4a00-afa2-b54a1480722a · outbound

This paper cites Blind im- age quality assessment: From natural scene statistics to per- ceptual quality.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Blind im- age quality assessment: From natural scene statistics to per- ceptual quality

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0b8c3bde-7316-4e99-badc-79a6f0a0cba0 · outbound

This paper cites A no-reference im- age blur metric based on the cumulative probability of blur detection (cpbd).

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation A no-reference im- age blur metric based on the cumulative probability of blur detection (cpbd)

Reference 31

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raw_fallback, observed 2026-08-06T15:29:16.697043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a0a56354-913b-4970-ac5a-8b02a14de018 · outbound

This paper cites Sdd-fiqa: unsupervised face image quality assess- ment with similarity distribution distance.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Sdd-fiqa: unsupervised face image quality assess- ment with similarity distribution distance

Reference 32

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Source-reported events for the cited work

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Observation 88b08012-d188-457e-b6c7-11c761240a31 · outbound

This paper cites Statistics of natural images: Scaling in the woods.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Statistics of natural images: Scaling in the woods

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation dcbd762a-42b3-48d4-a883-6d9d481325ad · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3b0fa87c-7edb-43ac-96fe-0a119914fbf0 · outbound

This paper cites Face image quality assessment: A literature survey.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Face image quality assessment: A literature survey

Reference 35

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raw_fallback, observed 2026-08-06T15:29:15.919572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:08.570391Z digest=sha256:1bc226bcf43511fce79fb80916a3574080f2767b12eed0df38550cf1f302acff

Observation 6f2d5402-d0e5-43a1-8454-e309637c743f · outbound

This paper cites Gray Level Co-Occurrence Matrices: Generalisation and Some New Features.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Gray Level Co-Occurrence Matrices: Generalisation and Some New Features

Reference 36

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verified exact
local_arxiv, observed 2026-08-06T15:29:11.608763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:08.669011Z digest=sha256:3d29450721e26dd2e4d3020ee9a8726be20b40837318a068e6e8cc3763fbf1f2

Observation 0fd3eecf-0ca7-4239-bf5c-ca59bb5fc2c5 · outbound

This paper cites Going the extra mile in face image quality assess- ment: A novel database and model.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Going the extra mile in face image quality assess- ment: A novel database and model

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:15.736227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:08.713072Z digest=sha256:55f0af2283ed36fd9b4ed603820390514b35f55984b2806e6d76717d1034bd47

Observation 353b34c4-8112-4b8e-b4b9-1b7aa6b9f34f · outbound

This paper cites Mc360iqa: A multi-channel cnn for blind 360-degree image quality assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Mc360iqa: A multi-channel cnn for blind 360-degree image quality assessment

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:15.585223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:08.812327Z digest=sha256:a207141ce3bfe0d484a91a8081c3e153924d977c3acc8e9cfa31eef0a0839f92

Observation 7b765838-f9f7-4cb4-8dd9-39832328b4cd · outbound

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

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Deep learning based full-reference and no-reference quality assessment models for compressed ugc videos

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:15.431951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:08.871381Z digest=sha256:3eb36f80b7f021092159faf757ec0a688a2825a316a8035696a45ac5ce9f9014

Observation c5a14cbe-355d-49be-81d5-8cd44fc9ca44 · outbound

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

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation A deep learning based no-reference quality assessment model for ugc videos

Reference 40

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unresolved
no resolver link, observed 2026-08-06T15:29:08.944653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:08.944653Z digest=sha256:fee8bda0f157fe87993dff5fb37a2a611f0091dc1adc89c3a09766056feb2136

Observation 0f979179-230f-4a46-bcd7-05e79b3c6651 · outbound

This paper cites Blind quality assessment for in-the-wild images via hierarchical feature fusion and iterative mixed database training.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Blind quality assessment for in-the-wild images via hierarchical feature fusion and iterative mixed database training

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:15.264157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:09.011508Z digest=sha256:7d384f2842dbe2c32952cc28dbae22567c76ad4ec2acd9cab48b687b26e9edfe

Observation 7c323b06-ed24-49da-bff9-01eaf2d4ab17 · outbound

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

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Enhancing blind video quality as- sessment with rich quality-aware features

Reference 42

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:09.072718Z digest=sha256:a5677519ea8fc954304dd82bc4be88af91f3e34bafc11a2d53956214312e4988

Observation e08d2744-0802-4d99-ad27-fb7cdd18a14c · outbound

This paper cites Assessing uhd image quality from aesthetics, distor- tions, and saliency.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Assessing uhd image quality from aesthetics, distor- tions, and saliency

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:15.087481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:09.141008Z digest=sha256:6f79959089d115a548cf413911c99a279587761c5a3a2e0aab493908f2e9f9a1

Observation 7423cacf-f57c-4f6d-a67f-627eff2459d5 · outbound

This paper cites Dual-Branch Network for Portrait Image Quality Assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Dual-Branch Network for Portrait Image Quality Assessment

Reference 44

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:09.208893Z digest=sha256:8f8319f38f4f911b1c6b370f4f522f8173eea57b887bde6d7414d8e6905a6cc9

Observation 28b78869-cd6d-4687-a215-d6016068f751 · outbound

This paper cites ICME 2025 Generalizable HDR and SDR Video Quality Measurement Grand Challenge.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation ICME 2025 Generalizable HDR and SDR Video Quality Measurement Grand Challenge

Reference 45

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unresolved
no resolver link, observed 2026-08-06T15:29:09.284389Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:09.284389Z digest=sha256:755aaffd5da092d44548e5774cf9823b3510564a7f64482b0d3db96ad33b358a

Observation 8fb5aa81-8558-46a6-b908-f544ad9d58ce · outbound

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

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation An empirical study for efficient video quality assessment

Reference 46

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:09.380552Z digest=sha256:7a750802a599d528f4363242b9cd6c0474d045171efa64cd6190b5db8c02ff28

Observation 456641a8-432d-46fc-892f-c59c30d9c18a · outbound

This paper cites Ser-fiq: Unsupervised esti- mation of face image quality based on stochastic embedding robustness.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Ser-fiq: Unsupervised esti- mation of face image quality based on stochastic embedding robustness

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:14.921307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:09.462066Z digest=sha256:fdced08c30b0ab9b71f5fceb1240ff3ff47a62e96766a5b0e7e48c5ca3ac403c

Observation 9ab6c32e-1fab-4eec-bf9b-6b63219ece23 · outbound

This paper cites S3: A spectral and spatial sharpness measure.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation S3: A spectral and spatial sharpness measure

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:14.683411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:09.524568Z digest=sha256:4499ec4def46e970d4e3c3ae36ebbcf0323bb93be10c4a679a2ebe4a0c1acd31

Observation dd5e0af3-cd6b-4b5b-ab92-33c05ef8001e · outbound

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

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Ex- ploring clip for assessing the look and feel of images

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:14.457906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:09.603523Z digest=sha256:ce3c0e0770ffc7fb4452c98e7e0c7d9ca95129fff737d329ea442a0fbcf4fd23

Observation fc8f06fb-da6b-4c28-ba98-da1c3827cf45 · outbound

This paper cites Large multi-modality model assisted ai-generated image quality as- sessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Large multi-modality model assisted ai-generated image quality as- sessment

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:29:14.250301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:09.668653Z digest=sha256:3381f7175e090cf314b3b47a8c69cbf6669f692a7449a70f8b570435efe695de

Observation dc5250f2-9ec6-436a-8dcb-b307e3f6ab54 · outbound

This paper cites Q-align: Teaching lmms for visual scoring via discrete text-defined levels.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Q-align: Teaching lmms for visual scoring via discrete text-defined levels

Reference 51

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:14.083722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:09.731394Z digest=sha256:8acfd57515cd9bc9e4154877819d863ddc2ced390c6ff54cbd5a10f5a0307a15

Observation ec9b3f12-ca7d-41ad-b3df-2c45517a12d2 · outbound

This paper cites Fvq: A large-scale dataset and a lmm-based method for face video quality assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Fvq: A large-scale dataset and a lmm-based method for face video quality assessment

Reference 52

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:09.806049Z digest=sha256:2b963b5f63c39b0a72bb15dc80d3cfc7df76086baddedb375d93285ac42f73c9

Observation 20b98541-ebba-4d3b-95b2-e4d47f3aa53d · outbound

This paper cites Self-training with noisy student improves imagenet clas- sification.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Self-training with noisy student improves imagenet clas- sification

Reference 53

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:09.899849Z digest=sha256:95291f78ff5ed077612a80604c924a614f930c2b93ceb0ff0fa6bff01fc7622d

Observation 5e9cb024-cd84-4420-8e4e-8b61b7ee6836 · outbound

This paper cites Billion-scale semi-supervised learning for image classification.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Billion-scale semi-supervised learning for image classification

Reference 54

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no resolver link, observed 2026-08-06T15:29:09.976461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:09.976461Z digest=sha256:5f50e7480d80a3118ca304770c2d0061ea98df0a39401c2db477d899cfc1a6b8

Observation 991cae4e-1f8b-4838-a9c5-413009f4d96c · outbound

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

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Maniqa: Multi-dimension attention network for no-reference image quality assessment

Reference 55

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source=pdf_text observed=2026-08-06T15:29:10.067122Z digest=sha256:ea81d035bb00f52dbd10bc5961116739e4fde3e9f853b7f2eb51ae32855e1b37

Observation 30c80f60-7792-401a-9398-206ea9b3bc3d · outbound

This paper cites Attention based network for no- reference ugc video quality assessment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Attention based network for no- reference ugc video quality assessment

Reference 56

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:13.911550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.147137Z digest=sha256:4f467ad9051432b2b708597f97ae0f94acf78fcce068df827110762f60850b84

Observation 3ef4cc19-7318-464b-b930-7754277d1a0c · outbound

This paper cites Perceptual image quality assessment: a survey.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Perceptual image quality assessment: a survey

Reference 57

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raw_fallback, observed 2026-08-06T15:29:13.707817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.217442Z digest=sha256:7e45fc00302ea78919b9ff3774e9234b17e7cadaa51e6c8516e6b767535c43db

Observation d8094df4-be2b-450d-9811-7a5a6c925652 · outbound

This paper cites A psychovisual quality metric in free-energy principle.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation A psychovisual quality metric in free-energy principle

Reference 58

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:13.476233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.325537Z digest=sha256:cf12ef8a7b97f77f35bb609ff8b4c5a68efd892835a52fed26105ff92c4e1565

Observation 9933eeac-22db-4b7d-9051-e4288077b811 · outbound

This paper cites Perceptual quality assessment of low-light image enhance- ment.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Perceptual quality assessment of low-light image enhance- ment

Reference 59

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:13.211664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.387022Z digest=sha256:1202cb6f3e7f8c098c87d55e6d1a443cec06ad0e04f86c8e0bdbc7e93b18524b

Observation 52abbc73-05c4-4558-b6a2-7ad858a42b5b · outbound

This paper cites Blind image quality assessment via vision- language correspondence: A multitask learning perspective.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Blind image quality assessment via vision- language correspondence: A multitask learning perspective

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:29:12.961257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.459568Z digest=sha256:88771df6544e007826ec07c2555e24c0392fe7617eb515429e86b2881ad3b332

Observation 9a30edc4-5435-4460-964e-efb9ab60b23e · outbound

This paper cites A no-reference evalu- ation metric for low-light image enhancement.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation A no-reference evalu- ation metric for low-light image enhancement

Reference 61

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:12.660174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.538007Z digest=sha256:dbbaba8181db352d41e630f3bc3ab2292f8b9a6ccb91eaceb2716dc6954e435e

Observation afbc08c0-5411-4200-8256-3755a0808f44 · outbound

This paper cites A no-reference deep learning quality assessment method for super-resolution im- ages based on frequency maps.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation A no-reference deep learning quality assessment method for super-resolution im- ages based on frequency maps

Reference 62

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:12.404967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.604625Z digest=sha256:3cd7cd1a2f12b948d1516e54f671affd46dcab1e56c10fc7691a16b48e343076

Observation e3567aee-4f4b-4af0-bb95-74c89ee0009b · outbound

This paper cites Md-vqa: Multi-dimensional quality assessment for ugc live videos.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Md-vqa: Multi-dimensional quality assessment for ugc live videos

Reference 63

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:12.114609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.674582Z digest=sha256:5c18640a9d00d4abe165d0f8ebb172f9f664851d0f966e21f9c66c839e2ada49

Observation 8d29674c-8c89-454a-88ac-98860673220b · outbound

This paper cites Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model

Reference 64

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unresolved
no resolver link, observed 2026-08-06T15:29:10.750858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:10.750858Z digest=sha256:1f58f3205d33f5a1504f5d5d84e5f97c4a1d747d74980453effb11b527aac5f8

Observation f6520ac5-cb40-4d62-9de5-94d090731953 · outbound

This paper cites Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric

Reference 65

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unresolved
no resolver link, observed 2026-08-06T15:29:10.862485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:10.862485Z digest=sha256:c6db5919a2396bcebeb0c8831036b8152b1c47d287cbdf1b8ada9a60a335a598

Observation 3feb4ea5-b13f-44ff-9b97-99d98466a8d2 · outbound

This paper cites Advancing zero-shot digital human quality assessment through text-prompted evaluation.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Advancing zero-shot digital human quality assessment through text-prompted evaluation

Reference 66

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verified fuzzy
raw_fallback, observed 2026-08-06T15:29:11.892480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:29:10.925897Z digest=sha256:cfa901aa7549dce211d3693d1cb770b207b59b619af527a03ed091da6cab9dfa

Observation 96581f73-bd66-413f-bda8-f9f61362e722 · outbound

This paper cites Vquala 2025 challenge on visual quality comparison for large multimodal models: Methods and results.

Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation Vquala 2025 challenge on visual quality comparison for large multimodal models: Methods and results

Reference 67

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no resolver link, observed 2026-08-06T15:29:11.031879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:11.031879Z digest=sha256:5e72e10c0d084aa5a4f1af6456d6e89e6c44f07d6506740f645a206915c2d232

Pith citing papers

No inbound Pith citation observations are available.