{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/consistent-teacher-provides-better-1","title":"Consistent-Teacher: Towards Reducing Inconsistent Pseudo-targets in Semi-supervised Object Detection","arxiv_id":"2209.01589","date":"2022-09-04","proceeding":"CVPR 2023 1","authors":["Xinjiang Wang","Xingyi Yang","Shilong Zhang","Yijiang Li","Litong Feng","Shijie Fang","Chengqi Lyu","Kai Chen","Wayne Zhang"],"abstract":"In this study, we dive deep into the inconsistency of pseudo targets in semi-supervised object detection (SSOD). Our core observation is that the oscillating pseudo-targets undermine the training of an accurate detector. It injects noise into the student's training, leading to severe overfitting problems. Therefore, we propose a systematic solution, termed ConsistentTeacher, to reduce the inconsistency. First, adaptive anchor assignment~(ASA) substitutes the static IoU-based strategy, which enables the student network to be resistant to noisy pseudo-bounding boxes. Then we calibrate the subtask predictions by designing a 3D feature alignment module~(FAM-3D). It allows each classification feature to adaptively query the optimal feature vector for the regression task at arbitrary scales and locations. Lastly, a Gaussian Mixture Model (GMM) dynamically revises the score threshold of pseudo-bboxes, which stabilizes the number of ground truths at an early stage and remedies the unreliable supervision signal during training. ConsistentTeacher provides strong results on a large range of SSOD evaluations. It achieves 40.0 mAP with ResNet-50 backbone given only 10% of annotated MS-COCO data, which surpasses previous baselines using pseudo labels by around 3 mAP. When trained on fully annotated MS-COCO with additional unlabeled data, the performance further increases to 47.7 mAP. Our code is available at \\url{https://github.com/Adamdad/ConsistentTeacher}.","url_abs":"https://arxiv.org/abs/2209.01589v3","url_pdf":"https://arxiv.org/pdf/2209.01589v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"consistent-teacher-provides-better-1","repo_url":"https://github.com/adamdad/consistentteacher","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"semi-supervised-object-detection","task_name":"Semi-Supervised Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/semi-supervised-object-detection-on-coco-1","task":"Semi-Supervised Object Detection","dataset":"COCO 1% labeled data","model":"Consistent-Teacher","rank_in_archive_order":5,"of":22,"metrics":{"mAP":"25.5"},"uses_additional_data":false},{"leaderboard":"/sota/semi-supervised-object-detection-on-coco-10","task":"Semi-Supervised Object Detection","dataset":"COCO 10% labeled data","model":"Consistent-Teacher","rank_in_archive_order":3,"of":27,"metrics":{"detector":"RetinaNet-Res50","mAP":"40.0"},"uses_additional_data":false},{"leaderboard":"/sota/semi-supervised-object-detection-on-coco-100","task":"Semi-Supervised Object Detection","dataset":"COCO 100% labeled data","model":"Consistent-Teacher","rank_in_archive_order":3,"of":13,"metrics":{"mAP":"48.20"},"uses_additional_data":true},{"leaderboard":"/sota/semi-supervised-object-detection-on-coco-2","task":"Semi-Supervised Object Detection","dataset":"COCO 2% labeled data","model":"Consistent-Teacher","rank_in_archive_order":2,"of":19,"metrics":{"mAP":"30.7"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2209.01589","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}