RGB+3D Anomaly Detection and Segmentation
7 papers with code • 1 benchmarks • 1 datasets
RGB+3D Anomaly Detection and Segmentation
Benchmarks
These leaderboards are used to track progress in RGB+3D Anomaly Detection and Segmentation
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MVTEC 3D-AD
Most implemented papers
The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization
We introduce the first comprehensive 3D dataset for the task of unsupervised anomaly detection and localization.
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.
Multimodal Industrial Anomaly Detection via Hybrid Fusion
2D-based Industrial Anomaly Detection has been widely discussed, however, multimodal industrial anomaly detection based on 3D point clouds and RGB images still has many untouched fields.
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation
vitjanz/3dsr
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(ii) We tackle the lack of diverse industrial depth datasets by introducing a simulation process for learning informative depth features in the depth encoder.
TransFusion -- A Transparency-Based Diffusion Model for Anomaly Detection
We reformulate the two-stage architecture into a single-stage iterative process that allows the exchange of information between the reconstruction and localization.
