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DepictQA: Depicted Image Quality Assessment with Vision Language Models DepictQA (Depicted image Quality Assessment) is dedicated to developing multi-modal image quality assessment models that linguistically assess or compare image quality, aiming to more closely align with human expressions. News [2025.11]    DepictQA-Wild (DepictQA-v2), also named Enhanced DepictQA (EDQA), was accepted to TIP. [2025.02]    DeQA-Score was accepted to CVPR 2025. [2025.01]    We released DeQA-Score, a distribution-based depicted image quality assessment model for score regression. Datasets, codes, and model weights (full tuning / LoRA tuning) were available. [2024.07]    Datasets (huggingface / modelscope) of DepictQA-v1 and DepictQA-Wild (DepictQA-v2) were available. [2024.07]    DepictQA-v1 was accepted to ECCV 2024. [2024.06]    Codes of DepictQA-v1 and DepictQA-Wild (DepictQA-v2) were available. [2024.05]    We released DepictQA-Wild (DepictQA-v2): a multi-functional in-the-wild descriptive image quality assessment model. [2023.12]    We released DepictQA-v1, a multi-modal image quality assessment model based on vision language models. Papers *: Equal Contribution, †: Corresponding Author Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distribution Zhiyuan You, Xin Cai, Jinjin Gu, Tianfan Xue†, Chao Dong† IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025 paper / project page / code / data We introduce DeQA-Score, a distribution-based depicted image quality assessment model for score regression. Enhancing Descriptive Image Quality Assessment with A Large-scale Multi-modal Dataset Zhiyuan You, Jinjin Gu, Xin Cai, Zheyuan Li, Kaiwen Zhu, Chao Dong†, Tianfan Xue† IEEE Transactions on Image Processing (TIP), 2025 paper / project page / code / data We introduce DepictQA-Wild, also named Enhanced DepictQA (EDQA), a multi-functional in-the-wild descriptive image quality assessment model. Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Models Zhiyuan You*, Zheyuan Li*, Jinjin Gu*, Zhenfei Yin, Tianfan Xue†, Chao Dong† European Conference on Computer Vision (ECCV), 2024 paper / project page / code / data We introduce DepictQA, leveraging Multi-modal Large Language Models, allowing for detailed, language-based, and human-like evaluation of image quality. Template from JonBarron