Methods › Computer Vision › Object Detection Models › RPDet

RPDet

2 papers tagged archive 2025-07-28

Introduced by Ze Yang et al. in RepPoints: Point Set Representation for Object Detection

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

RPDet, or RepPoints Detector, is a anchor-free, two-stage object detection model based on deformable convolutions. RepPoints serve as the basic object representation throughout the detection system. Starting from the center points, the first set of RepPoints is obtained via regressing offsets over the center points. The learning of these RepPoints is driven by two objectives: 1) the top-left and bottom-right points distance loss between the induced pseudo box and the ground-truth bounding box; 2) the object recognition loss of the subsequent stage.

PaperSourceSee Code · microsoft/RepPoints

Papers archive 2025-07-28

2 shown of 2, 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

3 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
Object1
Object Detection1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with RPDet: 2019 to 2022, peak 1 1 0 2019: 1 paper 2019 2020: 0 papers 2020 2021: 0 papers 2021 2022: 1 paper 2022
Papers per year the archive tags with this method, by the paper's archive date (2 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

Object Detection Models

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections