mlsanityData to 14 Oct 2026

Defect Spectrum: A Granular Look of Large-Scale Defect Datasets with Rich Semantics

arXiv 2310.17316 ↗First posted 26 Oct 2023cs.CVcited by 16

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Abstract (arXiv)

Defect inspection is paramount within the closed-loop manufacturing system. However, existing datasets for defect inspection often lack precision and semantic granularity required for practical applications. In this paper, we introduce the Defect Spectrum, a comprehensive benchmark that offers precise, semantic-abundant, and large-scale annotations for a wide range of industrial defects. Building on four key industrial benchmarks, our dataset refines existing annotations and introduces rich semantic details, distinguishing multiple defect types within a single image. Furthermore, we introduce Defect-Gen, a two-stage diffusion-based generator designed to create high-quality and diverse defective images, even when working with limited datasets. The synthetic images generated by Defect-Gen significantly enhance the efficacy of defect inspection models. Overall, The Defect Spectrum dataset demonstrates its potential in defect inspection research, offering a solid platform for testing and refining advanced models.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 34 of its 57 references that are in the map. First posted on arXiv 26 Oct 2023.

Builds on

34 of 57 references.

References · 34

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 4; 2025: 8; 2026: 3.

16 papers.

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  1. 2024MMAD: A Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detectioncited by 47
  2. 2023An Incremental Unified Framework for Small Defect Inspectioncited by 25
  3. 2024Unseen Visual Anomaly Generationcited by 23
  4. 2025TransPixeler: Advancing Text-to-Video Generation with Transparencycited by 12
  5. 2025ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detectioncited by 9
  6. 2024Few-shot Defect Image Generation based on Consistency Modelingcited by 8
  7. 2025A Survey on Industrial Anomaly Synthesiscited by 7
  8. 2024Small Object Few-shot Segmentation for Vision-based Industrial Inspectioncited by 5
  9. 2026AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectorscited by 4
  10. 2026Unification of Closed-Open Industrial Detection Scenarios: New Large-Scale Benchmarks,Challenges and Baselinescited by 3
  11. 2025STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignmentcited by 2
  12. 2025Sparse Data Diffusion for Scientific Simulations in Biology and Physicscited by 1
4 more
  1. 2025Compositional Attribute Imbalance in Vision Datasetscited by 1
  2. 2025Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Conceptscited by 1
  3. 2025FAST: Foreground-aware Diffusion with Accelerated Sampling Trajectory for Segmentation-oriented Anomaly Synthesiscited by 0
  4. 2026FuDU: A Fuzzy Dual-dimensional Uncertainty Framework for Streaming Active Learning in Industrial Defect Detectioncited by 0