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Object Detection in Computer Vision - Lecture 22

University of Central Florida via YouTube

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Provider

YouTube
Pricing

Free Video
Languages

English
Effort

59 minutes
Sessions

Self-Paced
Level

Intermediate

Found in

This lecture explains R-CNN, Fast R-CNN, and Faster R-CNN for object detection. It covers fine-tuning, feature extraction, classifier training, bounding box regression, ROI pooling, region proposal networks, and anchor boxes.

Syllabus

Intro
Which algorithm is better?
Detection as Classification
R-CNN Training (Fine-tuning)
R-CNN Training (feature extraction)
R-CNN Training (train classifier)
UCF R-CNN Training (bounding box regression/prediction)
Issue #1 with R-CNN
Fast R-CNN: Another view
Fast R-CNN: Region of Interest Pooling
ROI-Pooling
Problem of Fast R-CNN?
R-CNN Summary
Region proposal network (RPN)
Anchor boxes
Faster R-CNN