Pooling Operations

Center Pooling

Introduced by Duan et al. in CenterNet: Keypoint Triplets for Object Detection

Center Pooling is a pooling technique for object detection that aims to capture richer and more recognizable visual patterns. The geometric centers of objects do not necessarily convey very recognizable visual patterns (e.g., the human head contains strong visual patterns, but the center keypoint is often in the middle of the human body).

The detailed process of center pooling is as follows: the backbone outputs a feature map, and to determine if a pixel in the feature map is a center keypoint, we need to find the maximum value in its both horizontal and vertical directions and add them together. By doing this, center pooling helps the better detection of center keypoints.

Source: CenterNet: Keypoint Triplets for Object Detection

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🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

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