> ## Documentation Index
> Fetch the complete documentation index at: https://aegean.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# From R-CNN to Faster R-CNN

> Video references for the region-based detectors, from R-CNN through Fast R-CNN to Faster R-CNN, its PyTorch implementation and fine-tuning.

The region-based detectors in this group evolved in three steps. R-CNN classifies region proposals that an external algorithm produces, cropping and processing each one separately. Fast R-CNN runs the backbone once over the whole image and pools each proposal's features from the shared feature map. Faster R-CNN replaces the external proposals with a Region Proposal Network inside the detector. The sections that follow cover each step and then build Faster R-CNN in PyTorch.

## Video references

These videos, the first seven of the ExplainingAI series *Object Detection Tutorials: RCNN to YOLOv8*, follow the same path and pair well with the sections.

1. [Object Detection Series: Intro](https://www.youtube.com/watch?v=eoPMyROCsA0), a short trailer for the series.
2. [R-CNN Explained](https://www.youtube.com/watch?v=5DvljLV4S1E) (34 min).
3. [Mean Average Precision (mAP): Explanation and Implementation for Object Detection](https://www.youtube.com/watch?v=duBGmrxNHS8) (28 min), the metric the detectors are compared with. See also [Detection Metrics](/aiml-common/lectures/scene-understanding/object-detection/detection-metrics/index).
4. [Fast R-CNN Explained: ROI Pooling](https://www.youtube.com/watch?v=pCkxu9958bU) (33 min).
5. [Faster R-CNN Explanation: Region Proposal Network](https://www.youtube.com/watch?v=itjQT-gFQBY) (41 min).
6. [Faster R-CNN PyTorch Implementation](https://www.youtube.com/watch?v=Qq1yfWDdj5Y) (68 min).
7. [Faster R-CNN PyTorch Code Walkthrough: Fine-Tuning and Custom Dataset Training](https://www.youtube.com/watch?v=YA7BqiUTCwM) (63 min).

The [full playlist](https://www.youtube.com/playlist?list=PL8VDJoEXIjppNvOzocFbRciZBrtSMi81v) continues with YOLO, SSD and DETR.

***

<Callout icon="pen-to-square" iconType="regular">
  [Edit this page on GitHub](https://github.com/aegean-ai/eaia/edit/main/src/aiml-common/lectures/scene-understanding/object-detection/rcnn-introduction/index.mdx) or [file an issue](https://github.com/aegean-ai/eaia/issues/new/choose).
</Callout>


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.