# WildlifeReID-10k: Wildlife re-identification dataset with 10k individual animals

arXiv: https://arxiv.org/abs/2406.09211 · HTML: https://mlsanity.com/paper/2406.09211/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 66 references that are in the map.
- First posted on arXiv 13 Jun 2024.

## Builds on (most cited first, 16 of 16)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [DINOv2: Learning Robust Visual Features without Supervision](https://mlsanity.com/paper/2304.07193/) (2023)
- [A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks](https://mlsanity.com/paper/1610.02136/) (2016)
- [GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild](https://mlsanity.com/paper/1810.11981/) (2018)
- [Open-Set Recognition: a Good Closed-Set Classifier is All You Need?](https://mlsanity.com/paper/2110.06207/) (2021)
- [Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild"](https://mlsanity.com/paper/1908.07201/) (2019)
- [WildlifeDatasets: An open-source toolkit for animal re-identification](https://mlsanity.com/paper/2311.09118/) (2023)
- [Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Data](https://mlsanity.com/paper/1811.07749/) (2018)
- [Perspectives on individual animal identification from biology and computer vision](https://mlsanity.com/paper/2103.00560/) (2021)
- [Visual Identification of Individual Holstein-Friesian Cattle via Deep Metric Learning](https://mlsanity.com/paper/2006.09205/) (2020)
- [SeaTurtleID2022: A long-span dataset for reliable sea turtle re-identification](https://mlsanity.com/paper/2211.10307/) (2022)
- [NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation](https://mlsanity.com/paper/2005.13359/) (2020)
- [SealID: Saimaa ringed seal re-identification dataset](https://mlsanity.com/paper/2206.02260/) (2022)
- [Towards Self-Supervision for Video Identification of Individual Holstein-Friesian Cattle: The Cows2021 Dataset](https://mlsanity.com/paper/2105.01938/) (2021)
- [PixOOD: Pixel-Level Out-of-Distribution Detection](https://mlsanity.com/paper/2405.19882/) (2024)

## Built on by (most cited first, 19 of 19)

- [GorillaWatch: An Automated System for In-the-Wild Gorilla Re-Identification and Population Monitoring](https://mlsanity.com/paper/2512.07776/) (2025)
- [Finer-Personalization Rank: Fine-Grained Retrieval Examines Identity Preservation for Personalized Generation](https://mlsanity.com/paper/2512.19026/) (2025)
- [Wildlife Target Re-Identification Using Self-supervised Learning in Non-Urban Settings](https://mlsanity.com/paper/2507.02403/) (2025)
- [Nearest-Class Mean and Logits Agreement for Wildlife Open-Set Recognition](https://mlsanity.com/paper/2510.17338/) (2025)
- [Degradation-based augmented training for robust individual animal re-identification](https://mlsanity.com/paper/2603.04163/) (2026)
- [ID-Sim: An Identity-Focused Similarity Metric](https://mlsanity.com/paper/2604.05039/) (2026)
- [DS@GT ARC at AnimalCLEF 2026: Species-Aware Graph Construction for Multi-Species Animal Re-Identification](https://mlsanity.com/paper/2607.16453/) (2026)
- [PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers](https://mlsanity.com/paper/2506.14842/) (2025)
- [Not All Birds Look The Same: Identity-Preserving Generation For Birds](https://mlsanity.com/paper/2512.04485/) (2025)
- [Automated Re-Identification of Holstein-Friesian Cattle in Dense Crowds](https://mlsanity.com/paper/2602.15962/) (2026)
- [From Visual to Multimodal: Systematic Ablation of Encoders and Fusion Strategies in Animal Identification](https://mlsanity.com/paper/2603.02270/) (2026)
- [Centering Ecological Goals in Automated Identification of Individual Animals](https://mlsanity.com/paper/2604.20626/) (2026)
- [Multi-Object Tracking Consistently Improves Wildlife Inference](https://mlsanity.com/paper/2605.16672/) (2026)
- [Spotted: Location-informed Reidentification of Hyenas and Leopards in Camera Trap Surveys](https://mlsanity.com/paper/2607.00804/) (2026)
- [DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification](https://mlsanity.com/paper/2607.16644/) (2026)
- [Calibrated Similarity and Graph Clustering for Open-Set Animal Re-Identification](https://mlsanity.com/paper/2608.02469/) (2026)
- [VastMAT: A Large-Scale Multi-Category Benchmark for Multi-Animal Tracking](https://mlsanity.com/paper/2609.34390/) (2026)
- [FM-ReID: Selective Competitive Token Routing for Object Re-Identification](https://mlsanity.com/paper/2609.36560/) (2026)
- [Masked Swingers: Harnessing Data Augmentation to Advance Autoencoders for Self-Supervised Learning](https://mlsanity.com/paper/2609.38278/) (2026)

## Abstract (arXiv)

This paper introduces WildlifeReID-10k, a new large-scale re-identification benchmark with more than 10k animal identities of around 33 species across more than 140k images, re-sampled from 37 existing datasets. WildlifeReID-10k covers diverse animal species and poses significant challenges for SoTA methods, ensuring fair and robust evaluation through its time-aware and similarity-aware split protocol. The latter is designed to address the common issue of training-to-test data leakage caused by visually similar images appearing in both training and test sets. The WildlifeReID-10k dataset and benchmark are publicly available on Kaggle, along with strong baselines for both closed-set and open-set evaluation, enabling fair, transparent, and standardized evaluation of not just multi-species animal re-identification models.