Methods › Computer Vision › Object Detection Models › R-FCN

Region-based Fully Convolutional Network

R-FCN

32 papers tagged archive 2025-07-28

Introduced by Jifeng Dai et al. in R-FCN: Object Detection via Region-based Fully Convolutional Networks

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

Region-based Fully Convolutional Networks, or R-FCNs, are a type of region-based object detector. In contrast to previous region-based object detectors such as Fast/Faster R-CNN that apply a costly per-region subnetwork hundreds of times, R-FCN is fully convolutional with almost all computation shared on the entire image.

To achieve this, R-FCN utilises position-sensitive score maps to address a dilemma between translation-invariance in image classification and translation-variance in object detection.

PaperSourceSee Code · facebookresearch/Detectron

Papers archive 2025-07-28

30 shown of 32, 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 52 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 Detection24
object-detection22
Object18
Region Proposal4
General Classification3
Position3
image-classification3
Classification2
Deep Learning2
Image Classification2
Object Recognition2
Real-Time Object Detection2
Semantic Segmentation2
Traffic Sign Detection2
Transfer Learning2
2D Cyclist Detection1
2D Object Detection1
ARC1
Autonomous Vehicles1
Benchmarking1

Usage over time archive 2025-07-28

Papers per year tagged with R-FCN: 2016 to 2021, peak 9 9 0 2016: 3 papers 2016 2017: 9 papers 2017 2018: 9 papers 2018 2019: 5 papers 2019 2020: 4 papers 2020 2021: 2 papers 2021
Papers per year the archive tags with this method, by the paper's archive date (32 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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