mlsanityData to 14 Oct 2026

ENTIRe-ID: An Extensive and Diverse Dataset for Person Re-Identification

arXiv 2405.20465 ↗First posted 30 May 2024cs.CV cs.AI cs.LGcited by 5

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Abstract (arXiv)

The growing importance of person reidentification in computer vision has highlighted the need for more extensive and diverse datasets. In response, we introduce the ENTIRe-ID dataset, an extensive collection comprising over 4.45 million images from 37 different cameras in varied environments. This dataset is uniquely designed to tackle the challenges of domain variability and model generalization, areas where existing datasets for person re-identification have fallen short. The ENTIRe-ID dataset stands out for its coverage of a wide array of real-world scenarios, encompassing various lighting conditions, angles of view, and diverse human activities. This design ensures a realistic and robust training platform for ReID models. The ENTIRe-ID dataset is publicly available at https://serdaryildiz.github.io/ENTIRe-ID

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 10 of its 38 references that are in the map. First posted on arXiv 30 May 2024.

Builds on

10 of 38 references.

References · 10

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  3. 2021ByteTrack: Multi-Object Tracking by Associating Every Detection Boxcited by 823
  4. 2016Performance Measures and a Data Set for Multi-Target, Multi-Camera Trackingcited by 692
  5. 2017Person Transfer GAN to Bridge Domain Gap for Person Re-Identificationcited by 480
  6. 2021TransReID: Transformer-based Object Re-Identificationcited by 435
  7. 2016Person Re-identification in the Wildcited by 157
  8. 2019Unsupervised Tracklet Person Re-Identificationcited by 55
  9. 2021Large-Scale Spatio-Temporal Person Re-identification: Algorithms and Benchmarkcited by 47
  10. 2016Orientation Driven Bag of Appearances for Person Re-identificationcited by 8

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 2.

5 papers.

  1. 2025Towards Anytime Retrieval: A Benchmark for Anytime Person Re-Identificationcited by 5
  2. 2025Person detection and re-identification in open-world settings of retail stores and public spacescited by 1
  3. 2025CORE-ReID V2: Advancing the Domain Adaptation for Object Re-Identification with Optimized Training and Ensemble Fusioncited by 0
  4. 2026Towards Resolving Optimization Conflicts Between Image- and Text-Based Person Re-Identificationcited by 0
  5. 2026Misanthrope: A Privacy-Preserving Keypoint Detectorcited by 0