Methods › Computer Vision › One-Stage Object Detection Models › CenterNet

CenterNet

47 papers tagged archive 2025-07-28

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

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

CenterNet is a one-stage object detector that detects each object as a triplet, rather than a pair, of keypoints. It utilizes two customized modules named cascade corner pooling and center pooling, which play the roles of enriching information collected by both top-left and bottom-right corners and providing more recognizable information at the central regions, respectively. The intuition is that, if a predicted bounding box has a high IoU with the ground-truth box, then the probability that the center keypoint in its central region is predicted as the same class is high, and vice versa. Thus, during inference, after a proposal is generated as a pair of corner keypoints, we determine if the proposal is indeed an object by checking if there is a center keypoint of the same class falling within its central region.

PaperSourceSee Code · Duankaiwen/CenterNet

Papers archive 2025-07-28

30 shown of 47, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 70 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Object Detection31
object-detection29
Object18
Pose Estimation5
Keypoint Detection3
Representation Learning3
Semantic Segmentation3
Transfer Learning3
Clothes Landmark Detection2
Decoder2
Depth Estimation2
Domain Adaptation2
Instance Segmentation2
Keypoint Estimation2
Object Detection In Aerial Images2
Object Tracking2
Super-Resolution2
Triplet2
Unsupervised Domain Adaptation2
2D Human Pose Estimation1

Usage over time archive 2025-07-28

Papers per year tagged with CenterNet: 2019 to 2025, peak 10 10 0 2019: 5 papers 2019 2020: 8 papers 2020 2021: 10 papers 2021 2022: 8 papers 2022 2023: 6 papers 2023 2024: 9 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (47 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

One-Stage Object Detection ModelsObject Detection Models

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