Long Tailed Object Detection

Long-tail object detection is an important task in the field of computer vision, aiming to address the issue where head classes have abundant samples while tail classes have scarce samples in the training dataset. The goal of this task is to improve the model's detection performance on tail classes under a balanced test dataset, thereby achieving more comprehensive and accurate object recognition. The application value of long-tail object detection lies in enhancing the robustness and generalization ability of the model in real-world scenarios, especially in complex and diverse environments.