【論文筆記】：Group Sampling for Scale Invariant Face Detection
&Title Group Sampling for Scale Invariant Face Detection CVPR2019 &Summary 之前的網絡結構FPN和SSD，通常使用多個layer的不同空間精度預測不同規模的目標，簡言之，高精度圖預測小目標；作者發現沒有必要使用多個layer來預測不同規模的人臉，關鍵是要均衡不同規模的正樣例和負樣例的數量，作者就提出了分組採樣方法（a gro
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- 2. ICCV2017_S3FD：Single Shot Scale-invariant Face Detector
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相關文章
- 1. Group Sampling for Scale Invariant Face Detection閱讀筆記
- 2. ICCV2017_S3FD：Single Shot Scale-invariant Face Detector
- 3. 論文筆記--PCN:Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks
- 4. 論文筆記--PCN: Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks
- 5. 論文學習 AInnoFace：Accurate Face Detection for High Performance
- 6. 人臉檢測：《S3FD: Single Shot Scale-invariant Face Detector》論文詳解
- 7. Scale-Aware Face Detection
- 8. 論文筆記（一）【 Disentangled Representation Learning GAN for Pose-Invariant Face Recognition】
- 9. 人臉識別論文筆記 Reconstruction-Based Disentanglement for Pose-invariant Face Recognition
- 10. Reading Note: $ S^3FD $: Single Shot Scale-invariant Face Detector