Defect Transfer GAN: Diverse Defect Synthesis for Data Augmentation Article Swipe
Ruyu Wang
,
Sabrina Hoppe
,
Eduardo Monari
,
Marco F. Huber
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2302.08366
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2302.08366
Data-hunger and data-imbalance are two major pitfalls in many deep learning approaches. For example, on highly optimized production lines, defective samples are hardly acquired while non-defective samples come almost for free. The defects however often seem to resemble each other, e.g., scratches on different products may only differ in a few characteristics. In this work, we introduce a framework, Defect Transfer GAN (DT-GAN), which learns to represent defect types independent of and across various background products and yet can apply defect-specific styles to generate realistic defective images. An empirical study on the MVTec AD and two additional datasets showcase DT-GAN outperforms state-of-the-art image synthesis methods w.r.t. sample fidelity and diversity in defect generation. We further demonstrate benefits for a critical downstream task in manufacturing -- defect classification. Results show that the augmented data from DT-GAN provides consistent gains even in the few samples regime and reduces the error rate up to 51% compared to both traditional and advanced data augmentation methods.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2302.08366
- https://arxiv.org/pdf/2302.08366
- OA Status
- green
- Cited By
- 7
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4321277116
All OpenAlex metadata
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https://openalex.org/W4321277116Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2302.08366Digital Object Identifier
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Defect Transfer GAN: Diverse Defect Synthesis for Data AugmentationWork title
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preprintOpenAlex work type
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enPrimary language
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2023Year of publication
- Publication date
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2023-02-16Full publication date if available
- Authors
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Ruyu Wang, Sabrina Hoppe, Eduardo Monari, Marco F. HuberList of authors in order
- Landing page
-
https://arxiv.org/abs/2302.08366Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2302.08366Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2302.08366Direct OA link when available
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Computer science, Task (project management), High fidelity, Fidelity, Transfer (computing), Artificial intelligence, Pattern recognition (psychology), Biological system, Materials science, Parallel computing, Biology, Physics, Telecommunications, Economics, Acoustics, ManagementTop concepts (fields/topics) attached by OpenAlex
- Cited by
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7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 1, 2023: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.background | 74 |
| abstract_inverted_index.consistent | 136 |
| abstract_inverted_index.downstream | 120 |
| abstract_inverted_index.framework, | 58 |
| abstract_inverted_index.production | 17 |
| abstract_inverted_index.Data-hunger | 0 |
| abstract_inverted_index.approaches. | 11 |
| abstract_inverted_index.demonstrate | 115 |
| abstract_inverted_index.generation. | 112 |
| abstract_inverted_index.independent | 69 |
| abstract_inverted_index.outperforms | 100 |
| abstract_inverted_index.traditional | 155 |
| abstract_inverted_index.augmentation | 159 |
| abstract_inverted_index.manufacturing | 123 |
| abstract_inverted_index.non-defective | 25 |
| abstract_inverted_index.data-imbalance | 2 |
| abstract_inverted_index.classification. | 126 |
| abstract_inverted_index.defect-specific | 80 |
| abstract_inverted_index.characteristics. | 51 |
| abstract_inverted_index.state-of-the-art | 101 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.8399999737739563 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile |