Resolving Class Imbalance in Object Detection with Weighted Cross Entropy Losses

Understand

Object detection is an important task in computer vision which serves a lot of real-world applications such as autonomous driving, surveillance and robotics.

• Along with the rapid thrive of large-scale data, numerous state-of-the-art generalized object detectors (e.g.
• Faster R-CNN, YOLO, SSD) were developed in the past decade.
• Despite continual efforts in model modification and improvement in training strategies to boost detection accuracy, there are still limitations in performance of detectors when it comes to specialized datasets with uneven object class distributions.