Presentation by Sourish Ghosh, Andrew Saba, and Anish Bhattacharya, part of the Air Lab Summer School 2020.

Sessions list, overviews, and links to repos: https://theairlab.org/summer2020

This session is an overview of popular methods used for object detection and tracking. Platform tools used for neural network inference is also discussed.

Colab 1 (Test detectors): https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/object_detection.ipynb
Colab 2 (Implement ResNet): https://colab.research.google.com/drive/1aJ5t-54OTUL25NhQpuDEiEA2oh5U8n65?usp=sharing
Tracker example: https://bitbucket.org/castacks/tracker_tutorial_ws/

Outline:
0:00 – Intro
1:46 – Timeline of methods
2:50 – Image Classification (using AlexNet)
6:40 – Region Proposals
7:18 – Two-stage methods (R-CNN, Fast R-CNN, and Faster R-CNN)
14:41 – One-stage methods (YOLO, RetinaNet, CornerNet)
39:06 – DETR
46:50 – Summary of Object Detection
49:35 – Inference Platform Tools
54:01 – OpenVino
58:35 – TensorRT
1:03:07 – Object Tracking
1:07:57 – Correlation Filters and MOSSE
1:17:33 – Median Flow
1:20:50 – Tracking-Learning-Detection
1:27:28 – Conclusion

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