Methods › Computer Vision › Object Detection Models › VFNet

VarifocalNet

VFNet

8 papers tagged archive 2025-07-28

Introduced by Haoyang Zhang et al. in VarifocalNet: An IoU-aware Dense Object Detector

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

VarifocalNet is a method aimed at accurately ranking a huge number of candidate detections in object detection. It consists of a new loss function, named Varifocal Loss, for training a dense object detector to predict the IACS, and a new efficient star-shaped bounding box feature representation for estimating the IACS and refining coarse bounding boxes. Combining these two new components and a bounding box refinement branch, results in a dense object detector on the FCOS architecture, what the authors call VarifocalNet or VFNet for short.

PaperSource

Papers archive 2025-07-28

8 shown of 8, 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

12 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 Detection5
object-detection4
Object3
Sensitivity2
CPU1
General Classification1
Instance Segmentation1
Landmine1
Lesion Detection1
Semantic Segmentation1
Small Object Detection1
TAG1

Usage over time archive 2025-07-28

Papers per year tagged with VFNet: 2020 to 2025, peak 3 3 0 2020: 2 papers 2020 2021: 0 papers 2021 2022: 3 papers 2022 2023: 0 papers 2023 2024: 1 paper 2024 2025: 2 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (8 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

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