Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation | Paper Citation Record

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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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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

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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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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

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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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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

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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

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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

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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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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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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)

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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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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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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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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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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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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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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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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

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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

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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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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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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

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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

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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

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

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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

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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)

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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

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

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

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

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

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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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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

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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

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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

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

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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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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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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

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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

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