Datasets › noisy-ADE20K-Random

noisy-ADE20K-Random

Introduced by Juyeon Ko et al. in Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis26 Feb 2024 archive 2025-07-28

A new SIS benchmark designed to assess generation performance under noisy conditions, simulating human error that can occur during real-world applications. [Random] randomly adds an unlabeled class to the semantic maps, mimicing unintended user error and extreme random noise.

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
Noisy Semantic Image Synthesis noisy-ADE20K-Random SCDM FID 28.1 Stochastic Conditional Diffusion Models for Robust... mlvlab/scdm 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 1. 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
Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis 1 1 26 Feb 2024 ran 1 of 4 samples (3 unverified)

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • noisy-ADE20K-Random

1 variant name, as the archive lists them.

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