What is recorded here?
Studied component/augmentation combinations for efficient detection, then developed aggregation-aware scaling and reparameterization, lead-guided auxiliary labels, and programmable-gradient auxiliary branches with generalized layer aggregation.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Papers have different author sets and are not three versions of one single-authored manuscript. Training-only additions can raise training cost even when removed at inference. Original information-bottleneck motivation is not an independently established theorem that all task information is preserved. Inherited components retain credit.
Read the original work
- YOLOv4: Optimal Speed and Accuracy of Object Detection
- YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
- YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Alexey Bochkovskiy; Chien-Yao Wang; Hong-Yuan Mark Liao; I-Hau Yeh
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
YOLOv4/v7/v9: detector integration and auxiliary training pathways
Studied component/augmentation combinations for efficient detection, then developed aggregation-aware scaling and reparameterization, lead-guided auxiliary labels, and programmable-gradient auxiliary branches with generalized layer aggregation.
Scientific scope
Papers have different author sets and are not three versions of one single-authored manuscript. Training-only additions can raise training cost even when removed at inference. Original information-bottleneck motivation is not an independently established theorem that all task information is preserved. Inherited components retain credit.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Alexey Bochkovskiy; Chien-Yao Wang; Hong-Yuan Mark Liao; I-Hau Yeh
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.