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Semi-Supervised Object Detection

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Semi-supervised object detection uses both labeled data and unlabeled data for training. It not only reduces the annotation burden for training high-performance object detectors but also further improves the object detector by using a large number of unlabeled data.

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Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection

ClipGrader: Leveraging Vision-Language Models for Robust Label Quality Assessment in Object Detection

Semi-Supervised Weed Detection in Vegetable Fields: In-domain and Cross-domain Experiments

SimLTD: Simple Supervised and Semi-Supervised Long-Tailed Object Detection

Co-Learning: Towards Semi-Supervised Object Detection with Road-side Cameras

Collaborative Feature-Logits Contrastive Learning for Open-Set Semi-Supervised Object Detection

Applying the Lower-Biased Teacher Model in Semi-Supervised Object Detection

Semi-Supervised 3D Object Detection with Channel Augmentation using Transformation Equivariance

Class-balanced Open-set Semi-supervised Object Detection for Medical Images

Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformer

Multi-clue Consistency Learning to Bridge Gaps Between General and Oriented Object in Semi-supervised Detection

SOOD++: Leveraging Unlabeled Data to Boost Oriented Object Detection

Power of Cooperative Supervision: Multiple Teachers Framework for Enhanced 3D Semi-Supervised Object Detection

Collaboration of Teachers for Semi-supervised Object Detection

IMWA: Iterative Model Weight Averaging Benefits Class-Imbalanced Learning Tasks

Sparse Semi-DETR: Sparse Learnable Queries for Semi-Supervised Object Detection

Gradient-based Sampling for Class Imbalanced Semi-supervised Object Detection

Boosting Semi-Supervised Object Detection in Remote Sensing Images With Active Teaching

SeMoLi: What Moves Together Belongs Together

Detection of Thermal Events by Semi-Supervised Learning for Tokamak First Wall Safety

Credible Teacher for Semi-Supervised Object Detection in Open Scene

Mixed Pseudo Labels for Semi-Supervised Object Detection

Multiview Aerial Visual Recognition (MAVREC): Can Multi-view Improve Aerial Visual Perception?

Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection

LEOD: Label-Efficient Object Detection for Event Cameras

Weakly-semi-supervised object detection in remotely sensed imagery

Density-Guided Dense Pseudo Label Selection For Semi-supervised Oriented Object Detection

Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient ?

Navigating Data Heterogeneity in Federated Learning A Semi-Supervised Federated Object Detection

Rethinking Scale Imbalance in Semi-supervised Object Detection for Aerial Images

Semi-Supervised Object Detection with Uncurated Unlabeled Data for Remote Sensing Images

ALWOD: Active Learning for Weakly-Supervised Object Detection

Density Crop-guided Semi-supervised Object Detection in Aerial Images

Aligned Unsupervised Pretraining of Object Detectors with Self-training

Generalized Open-World Semi-Supervised Object Detection

Training-based Model Refinement and Representation Disagreement for Semi-Supervised Object Detection

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