mlsanityData to 14 Oct 2026

DAS3D: Dual-modality Anomaly Synthesis for 3D Anomaly Detection

arXiv 2410.09821 ↗First posted 13 Oct 2024cs.CVcited by 5

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Abstract (arXiv)

Synthesizing anomaly samples has proven to be an effective strategy for self-supervised 2D industrial anomaly detection. However, this approach has been rarely explored in multi-modality anomaly detection, particularly involving 3D and RGB images. In this paper, we propose a novel dual-modality augmentation method for 3D anomaly synthesis, which is simple and capable of mimicking the characteristics of 3D defects. Incorporating with our anomaly synthesis method, we introduce a reconstruction-based discriminative anomaly detection network, in which a dual-modal discriminator is employed to fuse the original and reconstructed embedding of two modalities for anomaly detection. Additionally, we design an augmentation dropout mechanism to enhance the generalizability of the discriminator. Extensive experiments show that our method outperforms the state-of-the-art methods on detection precision and achieves competitive segmentation performance on both MVTec 3D-AD and Eyescandies datasets.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 30 of its 50 references that are in the map. First posted on arXiv 13 Oct 2024.

Builds on

30 of 50 references.

References · 30

  1. 2013Describing Textures in the Wildcited by 2,125
  2. 2021Towards Total Recall in Industrial Anomaly Detectioncited by 776
  3. 2020PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localizationcited by 594
  4. 2021CutPaste: Self-Supervised Learning for Anomaly Detection and Localizationcited by 531
  5. 2021DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detectioncited by 514
  6. 2022Anomaly Detection via Reverse Distillation from One-Class Embeddingcited by 421
  7. 2021CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flowscited by 321
  8. 2020Sub-Image Anomaly Detection with Deep Pyramid Correspondencescited by 300
  9. 2020Multiresolution Knowledge Distillation for Anomaly Detectioncited by 285
  10. 2018Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoderscited by 264
  11. 2021FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flowscited by 227
  12. 2020Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flowscited by 212
18 more
  1. 2021The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localizationcited by 178
  2. 2022DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detectioncited by 154
  3. 2021Student-Teacher Feature Pyramid Matching for Anomaly Detectioncited by 146
  4. 2023Multimodal Industrial Anomaly Detection via Hybrid Fusioncited by 139
  5. 2022Registration based Few-Shot Anomaly Detectioncited by 133
  6. 2022Asymmetric Student-Teacher Networks for Industrial Anomaly Detectioncited by 117
  7. 2021Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localizationcited by 116
  8. 2022Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detectioncited by 93
  9. 2023Real3D-AD: A Dataset of Point Cloud Anomaly Detectioncited by 87
  10. 2022Omni-frequency Channel-selection Representations for Unsupervised Anomaly Detectioncited by 80
  11. 2023Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Networkcited by 67
  12. 2022Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptorscited by 66
  13. 2020Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Featurescited by 64
  14. 2023EasyNet: An Easy Network for 3D Industrial Anomaly Detectioncited by 43
  15. 2023Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulationcited by 33
  16. 2021Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localizationcited by 32
  17. 2022Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detectioncited by 18
  18. 2019Structuring Autoencoderscited by 11

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.

  1. 2025From Easy to Hard: Building a Shortcut for Differentially Private Image Synthesiscited by 7
  2. 20252D_3D Feature Fusion via Cross-Modal Latent Synthesis and Attention Guided Restoration for Industrial Anomaly Detectioncited by 4
  3. 20253D-PNAS: 3D Industrial Surface Anomaly Synthesis with Perlin Noisecited by 2
  4. 2025BridgeNet: A Unified Multimodal Framework for Bridging 2D and 3D Industrial Anomaly Detectioncited by 2
  5. 2026Neural Distribution Prior for LiDAR Out-of-Distribution Detectioncited by 0