Methods › Computer Vision › One-Stage Object Detection Models › YOLOv1

YOLOv1

6 papers tagged archive 2025-07-28

Introduced by Joseph Redmon et al. in You Only Look Once: Unified, Real-Time Object Detection

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

YOLOv1 is a single-stage object detection model. Object detection is framed as a regression problem to spatially separated bounding boxes and associated class probabilities. A single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation. Since the whole detection pipeline is a single network, it can be optimized end-to-end directly on detection performance.

The network uses features from the entire image to predict each bounding box. It also predicts all bounding boxes across all classes for an image simultaneously. This means the network reasons globally about the full image and all the objects in the image.

PaperSourceSee Code · pjreddie/darknet

Papers archive 2025-07-28

6 shown of 6, 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

13 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 Detection6
object-detection5
Object3
Real-Time Object Detection2
Autonomous Driving1
BIG-bench Machine Learning1
Blood Cell Count1
Blood Cell Detection1
CBC TEST1
Computational Efficiency1
Medical Diagnosis1
Object Counting1
Survey1

Usage over time archive 2025-07-28

Papers per year tagged with YOLOv1: 2015 to 2025, peak 2 2 0 2015: 1 paper 2015 2016: 0 papers 2016 2017: 0 papers 2017 2018: 0 papers 2018 2019: 2 papers 2019 2020: 0 papers 2020 2021: 0 papers 2021 2022: 0 papers 2022 2023: 0 papers 2023 2024: 2 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (6 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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