Datasets › PPM-100

PPM-100

Introduced by Zhanghan Ke et al. in MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition24 Nov 2020 archive 2025-07-28

PPM is a portrait matting benchmark with the following characteristics:

  • Fine Annotation - All images are labeled and checked carefully.
  • Natural Background - All images use the original background without replacement.
  • Rich Diversity - The images cover full/half body and various postures.
  • High Resolution - The resolution of images is between 1080p and 4k.

Dataset is created by authors of real-time matting model MODNet to measure performance for matting task.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Image Matting PPM-100 MODNet+ (Our) MAD 0.97 MODNet: Real-Time Trimap-Free Portrait Matting via... PaddlePaddle/PaddleSeg +8 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 9. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition 9 1 24 Nov 2020 not harvested

Dataset loaders archive 2025-07-28

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

Creative Commons Attribution NonCommercial ShareAlike 4.0

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • PPM-100

1 variant name, as the archive lists them.

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