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References (42)

[1]
Self-Evolving Vision-Language Models for Image Quality Assessment via Voting and Ranking
2025Wen Wen, Tianwu Zhi et al.
[2]
Deep Opinion-Unaware Blind Image Quality Assessment by Learning and Adapting from Multiple Annotators
2025Zhihua Wang, Xuelin Liu et al.
[3]
LMM4Edit: Benchmarking and Evaluating Multimodal Image Editing with LMMs
2025Zitong Xu, Huiyu Duan et al.
[4]
Leveraging Multimodal Large Language Models for Joint Discrete and Continuous Evaluation in Text-to-Image Alignment
2025Zhichao Zhang, Xinyue Li et al.
[5]
AGHI-QA: A Subjective-Aligned Dataset and Metric for AI-Generated Human Images
2025Yunhao Li, Sijing Wu et al.
[6]
LMM4LMM: Benchmarking and Evaluating Large-multimodal Image Generation with LMMs
2025Jiarui Wang, Huiyu Duan et al.
[7]
SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning
2024Zewen Chen, Juan Wang et al.
[8]
Vision-Language Consistency Guided Multi-Modal Prompt Learning for Blind AI Generated Image Quality Assessment
2024Jun Fu, Wei Zhou et al.
[9]
Opinion-Unaware Blind Image Quality Assessment Using Multi-Scale Deep Feature Statistics
2024Zhangkai Ni, Yue Liu et al.
[10]
Large Multi-modality Model Assisted AI-Generated Image Quality Assessment
2024Puyi Wang, Wei Sun et al.
[11]
AIGIQA-20K: A Large Database for AI-Generated Image Quality Assessment
2024Chunyi Li, Tengchuan Kou et al.
[12]
Quality-Aware Image-Text Alignment for Opinion-Unaware Image Quality Assessment
2024Lorenzo Agnolucci, L. Galteri et al.
[13]
A Comprehensive Study of Multimodal Large Language Models for Image Quality Assessment
2024Tianhe Wu, Kede Ma et al.
[14]
Deep Shape-Texture Statistics for Completely Blind Image Quality Evaluation
2024Yixuan Li, Peilin Chen et al.
[15]
Opinion Unaware Image Quality Assessment via Adversarial Convolutional Variational Autoencoder
2024Ankit Shukla, Avinash Upadhyay et al.
[16]
Transformer-based No-Reference Image Quality Assessment via Supervised Contrastive Learning
2023Jinsong Shi, Pan Gao et al.
[17]
ARNIQA: Learning Distortion Manifold for Image Quality Assessment
2023Lorenzo Agnolucci, L. Galteri et al.
[18]
AGIQA-3K: An Open Database for AI-Generated Image Quality Assessment
2023Chunyi Li, Zicheng Zhang et al.
[19]
Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild
2023Avinab Saha, Sandeep Mishra et al.
[20]
Quality-aware Pretrained Models for Blind Image Quality Assessment
2023Kai Zhao, Kun Yuan et al.

Showing 20 of 42 references

Founder's Pitch

"Develop a label-efficient image quality assessment tool using a distillation framework to minimize annotation costs."

Computer VisionScore: 6View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

4/4 signals

10

Series A Potential

2/4 signals

5

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