CFR-Net:Collaborative Feature Refinement Network for Medical Image Anomaly Detection

arXiv:2607.11509 · cs.CV · Submitted 2026-07-13 · Read on arXiv

cs.CV

Submitted: 2026-07-13

Updated: 2026-09-22

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Consistency — 34× in this paper · explained in 3 episodes
• Distillation — 19× in this paper · explained in 2 episodes
• Benchmark — 14× in this paper · explained in 2 episodes
• Knowledge Distillation — 7× in this paper · explained in 11 episodes
• Conference on Computer Vision and Pattern Recognition — 6× in this paper
• Ablation — 4× in this paper · explained in 1 episode
• Multi-Path Feature Refinement Module — 4× in this paper
• Ablation study — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Transformer — 3× in this paper · explained in 2 episodes
• Adaptability — 2× in this paper · explained in 1 episode
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Normalizing Flow — 2× in this paper · explained in 3 episodes
• Normalizing Flows — 2× in this paper · explained in 4 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adaptive Weighting — 1× in this paper · explained in 1 episode
• Area Under the Receiver Operating Characteristic Curve — 1× in this paper
• Calibration — 1× in this paper · explained in 7 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders
• Learning and Evaluating Representations for Deep One-class Classification
• AnoSeg: Anomaly Segmentation Network Using Self-Supervised Learning
• Unsupervised Visual Defect Detection with Score-Based Generative Model
• Student-Teacher Feature Pyramid Matching for Anomaly Detection

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models