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Found 3 papers, 3 papers with code
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly Detection
The success of knowledge distillation mainly relies on how to keep the feature discrepancy between the teacher and student model, in which it assumes that: (1) the teacher model can jointly represent two different distributions for the normal and abnormal patterns, while (2) the student model can only reconstruct the normal distribution.
HD2Reg: Hierarchical Descriptors and Detectors for Point Cloud Registration
Feature Descriptors and Detectors are two main components of feature-based point cloud registration.
HybridPoint: Point Cloud Registration Based on Hybrid Point Sampling and Matching
Firstly, we propose to use salient points with prominent local features as nodes to increase patch repeatability, and introduce some uniformly distributed points to complete the point cloud, thus constituting hybrid points.
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