</> Code with Papers by Syntology

Papers › MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised...

MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised Object Detection

16 Mar 2023CVPR 2023 1arXiv:2303.09061archive 2025-07-28

Liang Liu, Boshen Zhang, Jiangning Zhang, Wuhao Zhang, Zhenye Gan, Guanzhong Tian, Wenbing Zhu, Yabiao Wang, Chengjie Wang

Scale variation across object instances remains a key challenge in object detection task. Despite the remarkable progress made by modern detection models, this challenge is particularly evident in the semi-supervised case. While existing semi-supervised object detection methods rely on strict conditions to filter high-quality pseudo labels from network predictions, we observe that objects with extreme scale tend to have low confidence, resulting in a lack of positive supervision for these objects. In this paper, we propose a novel framework that addresses the scale variation problem by introducing a mixed scale teacher to improve pseudo label generation and scale-invariant learning. Additionally, we propose mining pseudo labels using score promotion of predictions across scales, which benefits from better predictions from mixed scale features. Our extensive experiments on MS COCO and PASCAL VOC benchmarks under various semi-supervised settings demonstrate that our method achieves new state-of-the-art performance. The code and models are available at \url{https://github.com/lliuz/MixTeacher}.

PaperPDFConference PDFCode

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

Code

lliuz/mixteacher officialmentioned in papermentioned on GitHubpytorchMIT report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

ObjectObject DetectionPseudo LabelSemi-Supervised Object Detectionobject-detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Semi-Supervised Object Detection COCO 1% labeled data MixTeacher-FRCNN mAP 25.16 #7 of 22 Archive leaderboard report
Semi-Supervised Object Detection COCO 1% labeled data MixTeacher-FCOS mAP 23.83 #9 of 22 Archive leaderboard report
Semi-Supervised Object Detection COCO 10% labeled data MixTeacher-FCOS detector FCOS-Res50 #8 of 27 Archive leaderboard report
Semi-Supervised Object Detection COCO 10% labeled data MixTeacher-FCOS mAP 36.95 #8 of 27 Archive leaderboard report
Semi-Supervised Object Detection COCO 10% labeled data MixTeacher-FRCNN detector FRCNN-Res50 #9 of 27 Archive leaderboard report
Semi-Supervised Object Detection COCO 10% labeled data MixTeacher-FRCNN mAP 36.72 #9 of 27 Archive leaderboard report
Semi-Supervised Object Detection COCO 2% labeled data MixTeacher-FRCNN mAP 29.11 #3 of 19 Archive leaderboard report
Semi-Supervised Object Detection COCO 2% labeled data MixTeacher-FCOS mAP 27.88 #8 of 19 Archive leaderboard report
Semi-Supervised Object Detection COCO 5% labeled data MixTeacher-FRCNN mAP 34.06 #5 of 23 Archive leaderboard report
Semi-Supervised Object Detection COCO 5% labeled data MixTeacher-FCOS mAP 33.42 #6 of 23 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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