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Lecture 11: Detection and Segmentation

Semantic Segmentation

• No objects, just pixels
• Input: Image
• Output: the decision of a category for every pixel. (각 픽셀이 어떤 category에 해당하는지)

Classification + Localization

• Singel object
• not only What the category is, but also Where is the object in the image?
• output: Bounding Box, label

Object Detection

• Multiple objects
• output: bounding box, label
• R-CNN -> Fast R-CNN -> Faster R-CNN
• Sliding window approach
• Region Proposals

Instance Segmentation

• Multiple objects
• bounding box 대신 segmentation

reference

[cs231n lecture 11: Detection and Segmentation](https://www.youtube.com/watch?v=nDPWywWRIRo&list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk&index=11)