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With the rapid advancement of Multi-modal Large Language Models (MLLMs), MLLM-based Image Quality Assessment (IQA) methods have shown promising performance in linguistic quality description.
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Xialei Liu, Joost van de Weijer, and Andrew D. Bagdanov · 2017
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Learning a no-reference quality metric for single-image super-resolution
Chao Ma, Chih-Yuan Yang, Xiaokang Yang, and Ming-Hsuan Yang · 2017
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Deep neural networks for no-reference and full-reference image quality assessment
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Blind predicting similar quality map for image quality assessment
Da Pan, Ping Shi, Ming Hou, Zefeng Ying, Sizhe Fu, and Yuan Zhang · 2018
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PieAPP: Perceptual image-error assessment through pairwise preference
Ekta Prashnani, Hong Cai, Yasamin Mostofi, and Pradeep Sen · 2018
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Hossein Talebi and Peyman Milanfar · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
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Harsh Agrawal, Karan Desai, Yufei Wang, Xinlei Chen, Rishabh Jain, Mark Johnson, Dhruv Batra, Devi Parikh, Stefan Lee, and Peter Anderson · 2019
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Decoupled weight decay regularization
Loshchilov Ilya and Hutter Frank · 2019
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KADID-10K: A large-scale artificially distorted iqa database
Hanhe Lin, Vlad Hosu, and Dietmar Saupe · 2019
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Incorporating semi-supervised and positive-unlabeled learning for boosting full reference image quality assessment
Yue Cao, Zhaolin Wan, Dongwei Ren, Zifei Yan, and Wangmeng Zuo · 2022
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Shift-tolerant perceptual similarity metric
Abhijay Ghildyal and Feng Liu · 2022
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Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan · 2022
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ChartQA: A benchmark for question answering about charts with visual and logical reasoning
Ahmed Masry, Xuan Long Do, Jia Qing Tan, Shafiq Joty, and Enamul Hoque · 2022
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Training language models to follow instructions with human feedback
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Image quality assessment: Unifying structure and texture similarity
Keyan Ding, Kede Ma, Shiqi Wang, and Eero P Simoncelli · 2020
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Perceptual quality assessment of smartphone photography
Yuming Fang, Hanwei Zhu, Yan Zeng, Kede Ma, and Zhou Wang · 2020
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Gu Jinjin, Cai Haoming, Chen Haoyu, Ye Xiaoxing, Jimmy S Ren, and Dong Chao · 2020
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Blindly assess image quality in the wild guided by a self-adaptive hyper network
Shaolin Su, Qingsen Yan, Yu Zhu, Cheng Zhang, Xin Ge, Jinqiu Sun, and Yanning Zhang · 2020
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GraphIQA: Learning distortion graph representations for blind image quality assessment
Simen Sun, Tao Yu, Jiahua Xu, Wei Zhou, and Zhibo Chen · 2022
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MANIQA: Multi-dimension attention network for no-reference image quality assessment
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Continual learning for blind image quality assessment
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GPT-4V(ision) system card, 2023
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InternLM: A multilingual language model with progressively enhanced capabilities
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mPLUG-Owl: Modularization empowers large language models with multimodality
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Lamm: Language-assisted multi-modal instruction-tuning dataset, framework, and benchmark
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PhoCoLens: Photorealistic and consistent reconstruction in lensless imaging
Xin Cai, Zhiyuan You, Hailong Zhang, Wentao Liu, Jinwei Gu, and Tianfan Xue · 2024
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ATTIQA: Generalizable image quality feature extractor using attribute-aware pretraining
Daekyu Kwon, Dongyoung Kim, Sehwan Ki, Younghyun Jo, Hyong-Euk Lee, and Seon Joo Kim · 2024
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mPLUG-Owl2: Revolutionizing multi-modal large language model with modality collaboration
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