Object Detection Modeling: 12 Visual Summaries

Hey Fastai friends, I thought the following content might interest some of you.

I’m at Day 23 of my 30 posts (on Object Detection) in 30 days challenge!
I gathered my 12 visual summaries (threads) on OD Modeling in the thread here below.

If you find those summaries helpful, please share to help others catch that content.

Summary:
1- Common Object Detector Architecture you should be familiar with

2- Four Feature Pyramid Network (FPN) Designs you should know

3- Seven things you should know about the Focal Loss

4- FCOS is the first anchor-free object detector that beat two-stage detectors

5- YOLOX beat YOLOv5!

6- How easy creating YOLOV5 and YOLOX models in IceVision

7- VFNet: A very interesting model that isn’t under the radar

8- YOLO Real-Time (YOLO-ReT) architecture targets edge devices

9- Similarities and the differences between some popular Object Detection models

10- FCOS3D won the 1st place out of all the vision-only methods in the nuScenes 3D Detection Challenge of NeurIPS 2020

11- The Generalized Intersection over Union (GIoU) can be used as a metric as well as a loss function

12- What is the Average Precision (AP), mean AP (mAP), and COCO Metric?

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