hi

1. Fully Convolutional Networks for
Semantic Segmentation
Mar 21, 2021
HeeDae Kwon

2. contents
• Introduction
• Related work
• Fully convolution networks
• Results

3. Introduction
Use FCN(fully convolution
network)
Trained end-to-end
Pre-training

4. Related
work
Fully convolution networks
Dense prediction with
convents

5. Fully convolution networks
• Adapting classifiers for dense
prediction
FC layer
- vanish spatial coordinates
Segmentation
Need location information
FC layer => FCN

6. Fully convolution networks
• Upsampling is backwards strided convolution
• Patchwise training is loss sampling

7. Results

8. Results

9. Results

10. 감사합니다