eliahuhorwitz/3D-ADS
Official Implementation for the "Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection" paper (VAND Workshop - CVPR 2023).
This project helps quality control and inspection engineers automatically detect defects on manufactured items using 3D scans. By analyzing depth maps and color images, it identifies anomalies in an object's shape, texture, or color. This tool takes 3D point cloud data or depth images of products as input and highlights specific areas where defects are present, helping quality inspectors quickly identify faulty goods.
137 stars. No commits in the last 6 months.
Use this if you need to reliably detect manufacturing defects like dents, scratches, or missing parts on products using 3D scanning, especially when traditional color-only methods miss geometric flaws.
Not ideal if your primary goal is to perform anomaly detection on standard 2D images without any depth or 3D structural information.
Stars
137
Forks
17
Language
Python
License
MIT
Category
Last pushed
Nov 28, 2022
Commits (30d)
0
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