3D Anomaly Detection
7 papers with code • 0 benchmarks • 4 datasets
3D-only Anomaly Detection
Benchmarks
These leaderboards are used to track progress in 3D Anomaly Detection
WALT
NovelCraft
Real 3D-AD
IoT-23
Most implemented papers
SplatPose & Detect: Pose-Agnostic 3D Anomaly Detection
Detecting anomalies in images has become a well-explored problem in both academia and industry.
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection
We utilize a recently introduced 3D anomaly detection dataset to evaluate whether or not using 3D information is a lost opportunity.
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection
We train a normalizing flow for density estimation as a teacher and a conventional feed-forward network as a student to trigger large distances for anomalies: The bijectivity of the normalizing flow enforces a divergence of teacher outputs for anomalies compared to normal data.
Shape-Guided: Shape-Guided Dual-Memory Learning for 3D Anomaly Detection
jayliu0313/Shape-Guided
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ICML 2023
We present a shape-guided expert-learning framework to tackle the problem of unsupervised 3D anomaly detection.
Real3D-AD: A Dataset of Point Cloud Anomaly Detection
m-3lab/real3d-ad
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NeurIPS 2023
High-precision point cloud anomaly detection is the gold standard for identifying the defects of advancing machining and precision manufacturing.
Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
This study explores the use of GPT-4V(ision), a powerful visual-linguistic model, to address anomaly detection tasks in a generic manner.
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
During testing, the point cloud repeatedly goes through the Mask Reconstruction Network, with each iteration's output becoming the next input.
