ID-aware Quality for Set-based Person Re-identification論文筆記
1. 摘要 針對set-based ReID問題，目前主流的一種做法是對set中的單張圖像使用CNN提取特徵，再對這些特徵使用融合算法整合爲set的特徵表示。但是，質量（作者定義了感知質量和語義質量，perceptually/semantically low quality images）較差的圖片和簡單圖片的過擬合會影響最終的特徵表示。因此，Wang等人提出了ID-aware q
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相關文章
- 1. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 2. 論文筆記：Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
- 3. Perceptual Quality Assessment of Smartphone Photography(論文筆記)
- 4. [論文筆記] Methodologies for Data Quality Assessment and Improvement (ACM Comput.Surv, 2009) (1)
- 5. RankIQA:Learning from Rankings for No-reference Image Quality Assessment論文閱讀筆記
- 6. [論文筆記] Methodologies for Data Quality Assessment and Improvement (ACM Comput.Surv, 2009) (2)
- 7. 《PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION》論文筆記
- 8. 《A High-Quality Denoising Dataset for Smartphone Cameras》論文筆記
- 9. 【論文筆記】Objects365: A Large-scale, High-quality Dataset for Object Detection（ICCV 2019）
- 10. Part-Aligned Bilinear Representations for Person Re-identification 論文筆記