R-CNN
1. Input image
2. Extract Region proposals - (sliding window, selective search)
3. Compute CNN features
4. Classify Regions
SPPNet
1. Input image
2. Compute CNN features
3. Spatial pyramid pooling
4. Classify Regions
Fast R-CNN
1. Inpute image
2. Compute CNN features
3. RoI projection (feature map의 RoI계산)
4. RoI Pooling을 통해 일정한 크기의 feature 추출
5. Classify Regions + Bounding Box Regressor(Smooth L1으로 loss계산)
Faster R-CNN - 현시점 끝판왕
1. Input image
2. Compute CNN features
3. RoI계산 (RPN(Region Proposal Network)이용 - anchor box 개념 사용 + selective search 대체)
4. NMS(Non Maximum Suppresion)
5. Classify Regions + Bounding Box Regressor(Smooth L1으로 loss계산)
SAM이 나와주길
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