Description
In this video, we take a look at Feature Pyramid Networks (FPN). What is it? How does it work? Why they are so useful in computer vision? Code included!
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[1 📚] Slides: https://link.excalidraw.com/p/readonly/yZO7bst7oS0CH0BgeZJ8
[2 📚] Code: https://github.com/ajhalthor/computer-vision-101/tree/main/feature_pyramid_network
[3 📚] Paper that introduced FPN: https://arxiv.org/pdf/1612.03144
Videos on topics discussed in the video for further details:
[1 📚] Sliding window object detection: https://youtu.be/Ocy54ea5Gd4?si=AJwyue7f-rLiYTAl
[2 📚] R-CNN: https://youtu.be/ZytVRaNE4cA?si=qMAxoNsJYrVSzqww
[3 📚] Fast R-CNN: https://youtu.be/rYLD9RLCqGo?si=SvSHDvwWOFtCRBij
[4 📚] Faster R-CNN: https://youtu.be/ws0nlxCWWI8?si=vNL1cSW-Cb73QmkF
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CHAPTERS
00:00 What are Feature Pyramid Networks?
00:50 Why we need FPNs with historical context
09:00 Computation of FPN
12:45 Training Faster R-CNN with FPN
17:00 How to select the appropriate tensor scale
19:46 Inference Faster R-CNN with FPN
21:40 Code showing the effectiveness of FPN on object detection
24:00 Quiz Time
24:53 Summary