Abstract — This paper studies the benefit of keypoint estimation on object detection. In particular, we focus on the paradigmatic one-stage and two-stage methods, two main categories in the object detection community. We note that while there has been remarkable progress on object detection and keypoint detection, insights on how the latter would benefit the former are somehow lacking. In this paper, we make two contributions. As a major contribution, we point out that one-stage and two-stage detectors have different abilities in accommodating keypoint description. The difference is clearly shown in our experiment where multiple detectors are compared in various detection tasks. Our essential observation is that one-stage detectors benefit consistently from the inclusion of a keypoint detection branch, while for two-stage detectors such benefit is obscure. As a minor contribution, we make several variant designs to improve the trade-off between efficiency and accuracy of the one-stage CenterNet on multiple detection tasks.