mlsanityData to 7 Oct 2026

RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification

arXiv 2006.12634 ↗First posted 22 Jun 2020cs.CVcited by 27

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Abstract (arXiv)

We introduce RP2K, a new large-scale retail product dataset for fine-grained image classification. Unlike previous datasets focusing on relatively few products, we collect more than 500,000 images of retail products on shelves belonging to 2000 different products. Our dataset aims to advance the research in retail object recognition, which has massive applications such as automatic shelf auditing and image-based product information retrieval. Our dataset enjoys following properties: (1) It is by far the largest scale dataset in terms of product categories. (2) All images are captured manually in physical retail stores with natural lightings, matching the scenario of real applications. (3) We provide rich annotations to each object, including the sizes, shapes and flavors/scents. We believe our dataset could benefit both computer vision research and retail industry. Our dataset is publicly available at https://www.pinlandata.com/rp2k_dataset.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Jun 2020.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 6; 2024: 6; 2025: 9; 2026: 4.

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  1. 2024TIPS: Text-Image Pretraining with Spatial awarenesscited by 37
  2. 2025ILIAS: Instance-Level Image retrieval At Scalecited by 29
  3. 2023Towards Universal Image Embeddings: A Large-Scale Dataset and Challenge for Generic Image Representationscited by 28
  4. 2023ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulationcited by 18
  5. 2024You Don't Need Domain-Specific Data Augmentations When Scaling Self-Supervised Learningcited by 16
  6. 2025Instance-Level Composed Image Retrievalcited by 12
  7. 2021Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scalescited by 11
  8. 2025MIEB: Massive Image Embedding Benchmarkcited by 11
  9. 2024UDON: Universal Dynamic Online distillatioN for generic image representationscited by 8
  10. 2023RetailKLIP : Finetuning OpenCLIP backbone using metric learning on a single GPU for Zero-shot retail product image classificationcited by 3
  11. 2026A Mixed Diet Makes DINO An Omnivorous Vision Encodercited by 3
  12. 2023Retail-786k: a Large-Scale Dataset for Visual Entity Matchingcited by 2
15 more
  1. 2024A Benchmark Grocery Dataset of Realworld Point Clouds From Single Viewcited by 2
  2. 2025Global-to-Local or Local-to-Global? Enhancing Image Retrieval with Efficient Local Search and Effective Global Re-rankingcited by 2
  3. 20226th Place Solution to Google Universal Image Embeddingcited by 1
  4. 2024Efficient and Discriminative Image Feature Extraction for Universal Image Retrievalcited by 1
  5. 2025UniFGVC: Universal Training-Free Few-Shot Fine-Grained Vision Classification via Attribute-Aware Multimodal Retrievalcited by 1
  6. 2025Instance-Level Generation for Representation Learningcited by 1
  7. 2026ELViS: Efficient Visual Similarity from Local Descriptors that Generalizes Across Domainscited by 1
  8. 2026Illuminating Visual Identity in Universal Multimodal Embeddingscited by 1
  9. 2023Concept-based Anomaly Detection in Retail Stores for Automatic Correction using Mobile Robotscited by 0
  10. 2023Classification of retail products: From probabilistic ranking to neural networkscited by 0
  11. 2024Hierarchical Knowledge Graph Construction from Images for Scalable E-Commercecited by 0
  12. 2025Hier-COS: Making Deep Features Hierarchy-aware via Composition of Orthogonal Subspacescited by 0
  13. 2025RoboBenchMart: Benchmarking Robots in Retail Environmentcited by 0
  14. 2025ZeBROD: Zero-Retraining Based Recognition and Object Detection Frameworkcited by 0
  15. 2026What Matters for Grocery Product Retrieval with Open Source Vision Language Modelscited by 0