tianyu0207/IGD
Official code for 'Deep One-Class Classification via Interpolated Gaussian Descriptor' [AAAI 2022 Oral]
This project helps identify unusual or defective items in a batch of images where most items are normal. You provide examples of what a 'normal' item looks like, and the system learns to spot deviations. This is useful for quality control inspectors or automated inspection systems in manufacturing.
Use this if you need to automatically detect anomalies or defects in visual data, such as products on an assembly line, without needing examples of what the defects look like.
Not ideal if you have detailed examples of all types of anomalies you want to detect, as more traditional supervised methods might be more suitable.
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Language
Python
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Last pushed
Oct 29, 2025
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