Semi-Supervised Object Detection
23 papers with code • 6 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Semi-Supervised Object Detection
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Libraries
Use these libraries to find Semi-Supervised Object Detection models and implementations
COCO 10% labeled data
Most implemented papers
A Simple Semi-Supervised Learning Framework for Object Detection
google-research/ssl_detection
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Semi-supervised learning (SSL) has a potential to improve the predictive performance of machine learning models using unlabeled data.
End-to-End Semi-Supervised Object Detection with Soft Teacher
microsoft/SoftTeacher
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ICCV 2021
This paper presents an end-to-end semi-supervised object detection approach, in contrast to previous more complex multi-stage methods.
Unbiased Teacher for Semi-Supervised Object Detection
facebookresearch/unbiased-teacher
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ICLR 2021
To address this, we introduce Unbiased Teacher, a simple yet effective approach that jointly trains a student and a gradually progressing teacher in a mutually-beneficial manner.
Label Matching Semi-Supervised Object Detection
hikvision-research/SSOD
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CVPR 2022
To remedy this issue, we present a novel label assignment mechanism for self-training framework, namely proposal self-assignment, which injects the proposals from student into teacher and generates accurate pseudo labels to match each proposal in the student model accordingly.
Consistency-based Semi-supervised Learning for Object detection
soo89/CSD-RFCN
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NeurIPS 2019
Making a precise annotation in a large dataset is crucial to the performance of object detection.
Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection
SYangDong/tse-t
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(1) The teacher model serves a dual role as a teacher and a student, such that the teacher predictions on unlabeled images may be very close to those of student, which limits the upper-bound of the student.
Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework
hattrickcr7/SoftTeacher
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CVPR 2021
To alleviate the confirmation bias problem and improve the quality of pseudo annotations, we further propose a co-rectify scheme based on Instant-Teaching, denoted as Instant-Teaching$^*$.
DETReg: Unsupervised Pretraining with Region Priors for Object Detection
Recent self-supervised pretraining methods for object detection largely focus on pretraining the backbone of the object detector, neglecting key parts of detection architecture.
MUM : Mix Image Tiles and UnMix Feature Tiles for Semi-Supervised Object Detection
Data augmentation strategy plays a significant role in the SSL framework since it is hard to create a weak-strong augmented input pair without losing label information.
MUM: Mix Image Tiles and UnMix Feature Tiles for Semi-Supervised Object Detection
jongmokkim/mix-unmix
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CVPR 2022
Data augmentation strategy plays a significant role in the SSL framework since it is hard to create a weak-strong augmented input pair without losing label information.
