This tutorial will introduce how to conduct research projects related to object detection efficiently with MMDetection 3.0 (https://github.com/open-mmlab/mmdetection). The contents will cover the following three parts:
1. This part will introduce object detection, instance segmentation, and panoptic segmentation. We will go through problem formulation, challenges, and representative methods in these fields.
2. In this part, we will introduce MMDetection, the OpenMMLab Detection Toolbox and Benchmark, which is also one of the most popular toolboxes in object detection and is the foundation of many toolboxes like MMDetection3D and MMTracking. We will go through the modular design and model zoo of MMDetection 3.0.
3. A hands-on tutorial that reveals how to play with MMDetection 3.0 to conduct model inference and training to facilitate research projects.

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