Feature Pyramid

Feature pyramids are hierarchical representations of image or other data features, designed to capture information at multiple scales and resolutions, improving the accuracy and robustness of various computer vision tasks. Current research focuses on integrating feature pyramids within transformer and convolutional neural network architectures, often employing bidirectional or multi-scale designs to enhance feature fusion and address limitations in handling small objects or fine-grained details. These advancements are significantly impacting object detection, segmentation, and other applications by improving accuracy and efficiency, particularly in challenging scenarios like medical image analysis and autonomous driving.