Semi-Supervised Object Detection
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Benchmarks
COCO 10% labeled data
COCO 5% labeled data
COCO 1% labeled data
COCO 2% labeled data
COCO 100% labeled data
COCO 0.5% labeled data
COCO
Most implemented
End-to-End Semi-Supervised Object Detection with Soft Teacher
A Simple Semi-Supervised Learning Framework for Object Detection
Efficient Teacher: Semi-Supervised Object Detection for YOLOv5
Unbiased Teacher for Semi-Supervised Object Detection
Semi-DETR: Semi-Supervised Object Detection with Detection Transformers
Label Matching Semi-Supervised Object Detection
Papers
DExTeR: Weakly Semi-Supervised Object Detection with Class and Instance Experts for Medical Imaging
Detecting anatomical landmarks in medical imaging is essential for diagnosis and intervention guidance. However, object detection models rely on costly bounding box annotations, limiting scalability. Weakly Semi-Supervis…
Semi-Supervised Object DetectionPractical Insights into Semi-Supervised Object Detection Approaches
Learning in data-scarce settings has recently gained significant attention in the research community. Semi-supervised object detection(SSOD) aims to improve detection performance by leveraging a large number of unlabeled…
Semi-Supervised Object DetectionFew-Shot LearningBuilding Blocks for Robust and Effective Semi-Supervised Real-World Object Detection
Semi-supervised object detection (SSOD) based on pseudo-labeling significantly reduces dependence on large labeled datasets by effectively leveraging both labeled and unlabeled data. However, real-world applications of S…
Autonomous DrivingData Augmentationobject-detectionObject Detection+2ClipGrader: Leveraging Vision-Language Models for Robust Label Quality Assessment in Object Detection
High-quality annotations are essential for object detection models, but ensuring label accuracy - especially for bounding boxes - remains both challenging and costly. This paper introduces ClipGrader, a novel approach th…
Objectobject-detectionObject DetectionPseudo Label+1Semi-Supervised Weed Detection in Vegetable Fields: In-domain and Cross-domain Experiments
Robust weed detection remains a challenging task in precision weeding, requiring not only potent weed detection models but also large-scale, labeled data. However, the labeled data adequate for model training is practica…
Semi-Supervised Object DetectionSimLTD: Simple Supervised and Semi-Supervised Long-Tailed Object Detection
Recent years have witnessed tremendous advances on modern visual recognition systems. Despite such progress, many vision models still struggle with the open problem of learning from few exemplars. This paper focuses on t…
Few-Shot Object DetectionLong-tailed Object DetectionObject DetectionSemi-Supervised Object Detection+1