mlsanityData to 14 Oct 2026

PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and Segmentation

arXiv 2307.04956 ↗First posted 11 Jul 2023cs.CVcited by 21

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Abstract (arXiv)

Visual anomaly detection is essential and commonly used for many tasks in the field of computer vision. Recent anomaly detection datasets mainly focus on industrial automated inspection, medical image analysis and video surveillance. In order to broaden the application and research of anomaly detection in unmanned supermarkets and smart manufacturing, we introduce the supermarket goods anomaly detection (GoodsAD) dataset. It contains 6124 high-resolution images of 484 different appearance goods divided into 6 categories. Each category contains several common different types of anomalies such as deformation, surface damage and opened. Anomalies contain both texture changes and structural changes. It follows the unsupervised setting and only normal (defect-free) images are used for training. Pixel-precise ground truth regions are provided for all anomalies. Moreover, we also conduct a thorough evaluation of current state-of-the-art unsupervised anomaly detection methods. This initial benchmark indicates that some methods which perform well on the industrial anomaly detection dataset (e.g., MVTec AD), show poor performance on our dataset. This is a comprehensive, multi-object dataset for supermarket goods anomaly detection that focuses on real-world applications.

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 32 of its 53 references that are in the map. First posted on arXiv 11 Jul 2023.

Builds on

32 of 53 references.

References · 32

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20 more
  1. 2018Real-world Anomaly Detection in Surveillance Videoscited by 577
  2. 2017Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discoverycited by 566
  3. 2019Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detectioncited by 564
  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
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 5; 2026: 11.

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  1. 2024MMAD: A Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detectioncited by 47
  2. 2024MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objectscited by 26
  3. 2024Long-Tailed Anomaly Detection with Learnable Class Namescited by 14
  4. 2025MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learningcited by 13
  5. 2026AD-Copilot: A Vision-Language Assistant for Industrial Anomaly Detection via Visual In-context Comparisoncited by 5
  6. 2025AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentationcited by 4
  7. 2026JUDO: A Juxtaposed Domain-Oriented Multimodal Reasoner for Industrial Anomaly QAcited by 4
  8. 2024MiniMaxAD: A Lightweight Autoencoder for Feature-Rich Anomaly Detectioncited by 3
  9. 2026Unification of Closed-Open Industrial Detection Scenarios: New Large-Scale Benchmarks,Challenges and Baselinescited by 3
  10. 2026AG-VAS: Anchor-Guided Zero-Shot Visual Anomaly Segmentation with Large Multimodal Modelscited by 1
  11. 2026MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Modelscited by 1
  12. 2026OPD-IAD: From Language Judgment to Industrial Anomaly Detection via On-Policy Self-Distillationcited by 1
9 more
  1. 2026VD-DeepStack: Bridging Visual Comparison and Language Reasoning for Few-Shot Anomaly Detectioncited by 1
  2. 2024MeLIAD: Interpretable Few-Shot Anomaly Detection with Metric Learning and Entropy-based Scoringcited by 0
  3. 2025Bi-Grid Reconstruction for Image Anomaly Detectioncited by 0
  4. 2025Noise Fusion-based Distillation Learning for Anomaly Detection in Complex Industrial Environmentscited by 0
  5. 2025Visual Anomaly Detection for Reliable Robotic Implantation of Flexible Microelectrode Arraycited by 0
  6. 2026CAD 100K: A Comprehensive Multi-Task Dataset for Car Related Visual Anomaly Detectioncited by 0
  7. 2026AnomalyClaw: A Universal Visual Anomaly Detection Agent via Tool-Grounded Refutationcited by 0
  8. 2026C3-Bench: A Context-Aware Change Captioning Benchmarkcited by 0
  9. 2026ADOPD: Reference-Privileged On-Policy Distillation for MLLM-Based Industrial Anomaly Detectioncited by 0