Defect Detection

35 papers with code • 5 benchmarks • 5 datasets

For automatic detection of surface defects in various products

Most implemented papers

Segmentation-Based Deep-Learning Approach for Surface-Defect Detection

skokec/segdec-net-jim2019 20 Mar 2019

This paper presents a segmentation-based deep-learning architecture that is designed for the detection and segmentation of surface anomalies and is demonstrated on a specific domain of surface-crack detection.

Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows

marco-rudolph/differnet 28 Aug 2020

To achieve a high robustness and performance we exploit multiple transformations in training and evaluation.

CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

microsoft/CodeXGLUE 9 Feb 2021

Benchmark datasets have a significant impact on accelerating research in programming language tasks.

CutPaste: Self-Supervised Learning for Anomaly Detection and Localization

Runinho/pytorch-cutpaste CVPR 2021

We aim at constructing a high performance model for defect detection that detects unknown anomalous patterns of an image without anomalous data.

Mixed supervision for surface-defect detection: from weakly to fully supervised learning

vicoslab/mixed-segdec-net-comind2021 13 Apr 2021

We also show that mixed supervision with only a handful of fully annotated samples added to weakly labelled training images can result in performance comparable to the fully supervised model's performance but at a significantly lower annotation cost.

A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection

shellysheynin/HTDG-model ICCV 2021

We demonstrate the superiority of our method on both the one-shot and few-shot settings, on the datasets of Paris, CIFAR10, MNIST and FashionMNIST as well as in the setting of defect detection on MVTec.

Deep Learning Based Steel Pipe Weld Defect Detection

huangyebiaoke/steel-pipe-weld-defect-detection 30 Apr 2021

Steel pipes are widely used in high-risk and high-pressure scenarios such as oil, chemical, natural gas, shale gas, etc.

DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detection

vitjanz/draem 17 Aug 2021

Visual surface anomaly detection aims to detect local image regions that significantly deviate from normal appearance.

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

salesforce/codet5 EMNLP 2021

We present CodeT5, a unified pre-trained encoder-decoder Transformer model that better leverages the code semantics conveyed from the developer-assigned identifiers.

Sequential Score Adaptation with Extreme Value Theory for Robust Railway Track Inspection

xavigibert/EvtTrack 20 Oct 2015

Periodic inspections are necessary to keep railroad tracks in state of good repair and prevent train accidents.