Methods › General › Prioritized Sampling › ATSS
Adaptive Training Sample Selection
ATSS
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Adaptive Training Sample Selection, or ATSS, is a method to automatically select positive and negative samples according to statistical characteristics of object. It bridges the gap between anchor-based and anchor-free detectors.
For each ground-truth box g on the image, we first find out its candidate positive samples. As described in Line $3$ to $6$, on each pyramid level, we select k anchor boxes whose center are closest to the center of g based on L2 distance. Supposing there are ℒ feature pyramid levels, the ground-truth box g will have k×ℒ candidate positive samples. After that, we compute the IoU between these candidates and the ground-truth g as 𝒟_g in Line $7$, whose mean and standard deviation are computed as m_g and v_g in Line $8$ and Line $9$. With these statistics, the IoU threshold for this ground-truth g is obtained as t_g=m_g+v_g in Line $10$. Finally, we select these candidates whose IoU are greater than or equal to the threshold t_g as final positive samples in Line $11$ to $15$.
Notably ATSS also limits the positive samples' center to the ground-truth box as shown in Line $12$. Besides, if an anchor box is assigned to multiple ground-truth boxes, the one with the highest IoU will be selected. The rest are negative samples.
Papers archive 2025-07-28
16 shown of 16, 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.
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HQOD: Harmonious Quantization for Object Detection 5 Aug 2024 · 1 repository · arXiv:2408.02561
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Generalized Mask-aware IoU for Anchor Assignment for Real-time Instance Segmentation 28 Dec 2023 · 0 repositories · arXiv:2312.17031
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Being Aware of Localization Accuracy By Generating Predicted-IoU-Guided Quality Scores 23 Sep 2023 · 1 repository · arXiv:2309.13269
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How to Train an Accurate and Efficient Object Detection Model on Any Dataset 30 Nov 2022 · 1 repository · arXiv:2211.17170
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DETRs with Collaborative Hybrid Assignments Training 22 Nov 2022 · 6 repositories · arXiv:2211.12860Syntology ran 0 of 5 samples · 5 unverified
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Sample hardness based gradient loss for long-tailed cervical cell detection 7 Aug 2022 · 0 repositories · arXiv:2208.03779
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RecursiveMix: Mixed Learning with History 14 Mar 2022 · 1 repository · arXiv:2203.06844
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Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation 19 Oct 2021 · 1 repository · arXiv:2110.09734
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TOOD: Task-aligned One-stage Object Detection 17 Aug 2021 · 6 repositories · arXiv:2108.07755Syntology ran 2 of 4 samples · 2 unverified · 2 pointer-only (licence)
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Disentangle Your Dense Object Detector 7 Jul 2021 · 2 repositories · arXiv:2107.02963
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Control Distance IoU and Control Distance IoU Loss Function for Better Bounding Box Regression 22 Mar 2021 · 1 repository · arXiv:2103.11696
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Implicit Feature Pyramid Network for Object Detection 25 Dec 2020 · 0 repositories · arXiv:2012.13563
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Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection 25 Nov 2020 · 5 repositories · arXiv:2011.12885
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RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder 29 Oct 2020 · 4 repositories · arXiv:2010.15831Syntology ran 0 of 5 samples · 5 unverified
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Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection 8 Jun 2020 · 7 repositories · arXiv:2006.04388Syntology ran 1 of 24 samples · 23 unverified
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Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection 5 Dec 2019 · 13 repositories · arXiv:1912.02424Syntology ran 0 of 4 samples · 4 unverified
Tasks archive 2025-07-28
20 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
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
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections