MPDD

Metal Parts Defect Detection Dataset

Dataset Information
Introduced
2021
License
Unknown
Homepage
Official Website
Contents

Overview

MPDD is a dataset aimed at benchmarking visual defect detection methods in industrial metal parts manufacturing. It consists of more than 1000 images with pixel-precise defect annotation masks. The dataset is divided into the training subset with anomaly-free samples and the validation subset that contains both normal and anomalous samples. The dataset can be downloaded at the following link.

Variants: MPDD

Associated Benchmarks

This dataset is used in 1 benchmark:

Recent Benchmark Submissions

Task Model Paper Date
Anomaly Detection CRAS Center-aware Residual Anomaly Synthesis for … 2025-05-23
Anomaly Detection KAnoCLIP KAnoCLIP: Zero-Shot Anomaly Detection through … 2025-01-07
Anomaly Detection PBAS Progressive Boundary Guided Anomaly Synthesis … 2024-12-23
Anomaly Detection ULSAD Revisiting Deep Feature Reconstruction for … 2024-10-21
Anomaly Detection DMDD Dual-Modeling Decouple Distillation for Unsupervised … 2024-08-07
Anomaly Detection AdaCLIP AdaCLIP: Adapting CLIP with Hybrid … 2024-07-22
Anomaly Detection GLASS A Unified Anomaly Synthesis Strategy … 2024-07-12
Anomaly Detection GLAD GLAD: Towards Better Reconstruction with … 2024-06-11
Anomaly Detection Dinomaly Dinomaly: The Less Is More … 2024-05-23
Anomaly Detection RealNet RealNet: A Feature Selection Network … 2024-03-09
Anomaly Detection POUTA Produce Once, Utilize Twice for … 2023-12-20
Anomaly Detection LeMO Towards Total Online Unsupervised Anomaly … 2023-05-25
Anomaly Detection DiffusionAD DiffusionAD: Norm-guided One-step Denoising Diffusion … 2023-03-15
Anomaly Detection PatchCore Towards Total Recall in Industrial … 2021-06-15

Research Papers

Recent papers with results on this dataset:

External Links: