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?