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

YOLOX

33 papers tagged archive 2025-07-28

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

YOLOX is a single-stage object detector that makes several modifications to YOLOv3 with a DarkNet53 backbone. Specifically, YOLO’s head is replaced with a decoupled one. For each level of FPN feature, we first adopt a 1 × 1 conv layer to reduce the feature channel to 256 and then add two parallel branches with two 3 × 3 conv layers each for classification and regression tasks respectively.

Additional changes include adding Mosaic and MixUp into the augmentation strategies to boost YOLOX’s performance. The anchor mechanism is also removed so YOLOX is anchor-free. Lastly, SimOTA for label assignment -- where label assignment is formulated as an optimal transport problem via a top-k strategy.

Source: YOLOX: Exceeding YOLO Series in 2021See Code · Megvii-BaseDetection/YOLOX

Papers archive 2025-07-28

30 shown of 33, 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 Detection25
object-detection21
Object17
Real-Time Object Detection8
2D Object Detection5
Multi-Object Tracking5
Autonomous Driving4
GPU4
Object Tracking4
Multiple Object Tracking3
Pedestrian Detection2
Scene Understanding2
Segmentation2
Video Object Detection2
3D Object Classification1
3D Object Reconstruction1
6D Pose Estimation using RGB1
Action Triplet Detection1
Action Triplet Recognition1
Benchmarking1

Usage over time archive 2025-07-28

Papers per year tagged with YOLOX: 2021 to 2025, peak 10 10 0 2021: 3 papers 2021 2022: 10 papers 2022 2023: 8 papers 2023 2024: 10 papers 2024 2025: 2 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (33 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 Models

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