RankIQA:Learning from Rankings for No-reference Image Quality Assessment論文閱讀筆記
根據本文題目中Image Quality Assessment可知，本文的研究方向是圖像質量評價，也就是給定一張圖片，輸出它的質量分數（或其他的評價標準，例如好壞等等） 根據數據集中未失真的圖片（reference image）或與之相關的信息是否可利用，將該研究方向的任務分爲三種: full-reference IQA(FR-IQA) reduced-reference IQA(RR-IQA)
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相關文章
- 1. Face-Image-Quality-Assessment
- 2. NIMA：Neural Image Assessment論文閱讀筆記
- 3. [閱讀筆記]Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and C
- 4. 文獻閱讀筆記5 On the Use of Deep Learning for Blind Image Quality Assessment（2D）
- 5. 文獻閱讀筆記6 Convolutional Neural Networks for No-Reference Image Quality Assessment（KANG）
- 6. 文獻閱讀筆記9 Full-reference quality assessment of stereopairs accounting for rivalry （Cyclopean image）
- 7. Perceptual Quality Assessment of Smartphone Photography(論文筆記)
- 8. 圖像質量評價相關論文閱讀筆記（二）：Controllable List-wise Ranking for Universal No-reference Image Quality Assessment
- 9. Tone-Mapped Image Quality Assessment
- 10. Image Quality Assessment,IQA and Video Quality Assessment,VQA