This document discusses feature pyramid networks for object detection. It introduces feature pyramid networks which use a bottom-up pathway to generate feature maps at multiple scales from a convolutional neural network and a top-down pathway that combines high-level and low-level semantic information. It then describes applying feature pyramid networks to region proposal networks and Fast/Faster R-CNN models for object detection and presents experimental results on using feature pyramid networks for region proposal and object detection.

1. Feature Pyramid Networks for
Object Detection
Mar 14, 2021
HeeDae Kwon

2. Contents
• Introduction
• Feature Pyramid Networks
• Experiments on Object Dectection

3. Introduction
Multi-scale feature
representation
Hierarchy network

4. Feature
Pyramid
Networks
Bottom-up pathway
=> ConvNet ,
Define pyramid level
Top-down pathway
=> upsampling

5. Application
• Feature Pyramid Networks for RPN
- single scale feature map => FPN
- use shared parameter
• Feature Pyramid Networks for Fast-RCNN

6. Experiments on Object Dectection
• Region Proposal with RPN

7. Experiments on Object Dectection
• Fast/Faster R-CNN

8. • 감사합니다