Datasets › WebFace260M

WebFace260M

Introduced by Zheng Zhu et al. in WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition6 Mar 2021 archive 2025-07-28

WebFace260M is a million-scale face benchmark, which is constructed for the research community towards closing the data gap behind the industry.

It consists of: - Noisy 4M identities and 260M faces - High-quality training data with 42M images of 2M identities by using automatic cleaning - A test set with rich attributes and a time-constrained evaluation protocol

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 20 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Custom (research-only)

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • WebFace260M

1 variant name, as the archive lists them.

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