CenterNet: Keypoint Triplets for Object Detection

Understand

In object detection, keypoint-based approaches often suffer a large number of incorrect object bounding boxes, arguably due to the lack of an additional look into the cropped regions.

• This paper presents an efficient solution which explores the visual patterns within each cropped region with minimal costs.
• We build our framework upon a representative one-stage keypoint-based detector named CornerNet.
• Our approach, named CenterNet, detects each object as a triplet, rather than a pair, of keypoints, which improves both precision and recall.