Localisation-Aware Uncertainty for Pretrained Object Detection

arXiv:2610.01409 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• Calibration — 36× in this paper · explained in 7 episodes
• Alignment — 18× in this paper · explained in 1 episode
• AUC — 15× in this paper · explained in 2 episodes
• Adversarial Attacks — 13× in this paper · explained in 1 episode
• Robustness — 10× in this paper · explained in 5 episodes
• Core — 8× in this paper · explained in 2 episodes
• Covariate Shift — 8× in this paper · explained in 2 episodes
• Uncertainty Quantification — 8× in this paper · explained in 8 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Adam — 4× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Epistemic Uncertainty — 3× in this paper · explained in 9 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Aleatoric Uncertainty — 2× in this paper · explained in 4 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Distribution Shift — 2× in this paper · explained in 5 episodes
• Monte Carlo dropout — 2× in this paper · explained in 2 episodes
• Success-Score Calibration Error — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Conformal Prediction — 1× in this paper · explained in 5 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Evidential Meta Model — 1× in this paper
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• International Joint Conference on Neural Networks — 1× in this paper
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems
• YOLOv11: An Overview of the Key Architectural Enhancements
• Towards Deep Learning Models Resistant to Adversarial Attacks

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