Distance to Class Prototypes: Active Learning for Object Detection

arXiv:2609.20248 · cs.CV · Submitted 2026-07-28 · Read on arXiv

cs.CV

Submitted: 2026-07-28

Updated: 2026-07-28

Terminology

• Active Learning — 66× in this paper · explained in 6 episodes
• Embeddings — 19× in this paper · explained in 2 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Computer Vision and Pattern Recognition — 8× in this paper
• Core — 6× in this paper · explained in 2 episodes
• International Conference on Computer Vision — 6× in this paper
• Adaptation — 5× in this paper · explained in 1 episode
• Contrastive Learning — 5× in this paper · explained in 5 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Aggregation — 4× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Domain Adaptation — 3× in this paper · explained in 5 episodes
• Monte Carlo dropout — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Active Object Detection — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Epistemic Uncertainty — 1× in this paper · explained in 10 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• Active Learning for Deep Object Detection
• ALBench: A Framework for Evaluating Active Learning in Object Detection
• Active Learning for Object Detection with Non-Redundant Informative Sampling
• DeLR: Active Learning for Detection with Decoupled Localization and Recognition Query
• Streamlining the Development of Active Learning Methods in Real-World Object Detection
• Active-SAOOD: Active Sparsely Annotated Oriented Object Detection in Remote Sensing Images

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