Object Detectors in the Open Environment: Challenges, Solutions, and Outlook

Understand

With the emergence of foundation models, deep learning-based object detectors have shown practical usability in closed set scenarios.

• However, for real-world tasks, object detectors often operate in open environments, where crucial factors (e.g., data distribution, objective) that influence model learning are often changing.
• The dynamic and intricate nature of the open environment poses novel and formidable challenges to object detectors.
• Unfortunately, current research on object detectors in open environments lacks a comprehensive analysis of their distinctive characteristics, challenges, and corresponding solutions, which hinders their secure deployment in critical real-world scenarios.