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README.md
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license: cc-by-4.0
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---
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license: cc-by-4.0
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language:
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- en
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tags:
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- computer-vision
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- anomaly-detection
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- industrial
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- defect-detection
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pretty_name: 'RobustAD: A Realworld Anomaly Detection Dataset for Robustness '
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size_categories:
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- 1K<n<10K
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---
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#About the Dataset
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RobustAD, specifically designed to evaluate the robustness of anomaly detection models in real-world scenarios. RobustAD features a curated dataset of defect detection images with meticulously controlled distribution shifts across multiple dimensions relevant to practical applications and more closely mirrors real-world deployment scenarios.
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RobustAD is designed to cover inspection challenges across multiple industries to ensure the diversity of use cases and
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encourage the development of generalizable methods. It is carefully curated to reflect the complexity of real-world
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anomaly detection task in terms of both the defect variations and the domain shifts captured in the data. Robus-
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tAD consists of 3 sub-datasets corresponding to 3 different objects of interest, each with a source domain data for
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training and multiple target domains with different shifts for testing.
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The PCB sub-dataset captures the challenges
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of finding subtle scratches, soldering melts, and missing parts which comprise of the most common defects encoun-
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tered during inspection of Printed Circuit Boards in electronics and semiconductor manufacturing. The metal parts
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sub-dataset reflects the challenges of inspecting metal automotive parts with reflective surfaces for possible chipping,
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dents, or porosity (holes in metal) in the automotive industry. The pile of packets represents a common count-based
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anomaly detection task performed by packaging machines in the pharmaceutical industry. We believe this broad cov-
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erage of tasks and anomaly types across important sectors ensures a general model that is relevant for common in-
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dustry inspection problems and serves as a good starting point. The PCB and metal parts datasets are defined for
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localization and classification tasks where as piled packets subset is only defined for classification task.
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#Dataset Card for RobustAD
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For more details, refer to this paper: COMING SOON!
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The three sub-datasets and the defects covered in each sub-dataset are listed below
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#How to Use
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TBD
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#License Information
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The RobustAD dataset is released under the Creative Commons license cc-by-4.0.
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#Citation Information
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COMING SOON!
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#Contact
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lppemula@amazon.com (Latha Pemula) | zdongqin@amazon.com (Dongqing Zhang) | onkardab@amazon.com (Onkar Dabeer)
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