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The ArtBench Dataset: Benchmarking Generative Models with Artworks

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arxiv 2206.11404 v1 pith:VW3MJ2PK submitted 2022-06-22 cs.CV cs.AIcs.LG

Peiyuan Liao , Xiuyu Li , Xihui Liu , Kurt Keutzer This is my paper
classification cs.CVcs.AIcs.LG
keywords artbench-10artworkdatasetimagesbenchmarkingartbenchclass-balanceddatasets
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We introduce ArtBench-10, the first class-balanced, high-quality, cleanly annotated, and standardized dataset for benchmarking artwork generation. It comprises 60,000 images of artwork from 10 distinctive artistic styles, with 5,000 training images and 1,000 testing images per style. ArtBench-10 has several advantages over previous artwork datasets. Firstly, it is class-balanced while most previous artwork datasets suffer from the long tail class distributions. Secondly, the images are of high quality with clean annotations. Thirdly, ArtBench-10 is created with standardized data collection, annotation, filtering, and preprocessing procedures. We provide three versions of the dataset with different resolutions ($32\times32$, $256\times256$, and original image size), formatted in a way that is easy to be incorporated by popular machine learning frameworks. We also conduct extensive benchmarking experiments using representative image synthesis models with ArtBench-10 and present in-depth analysis. The dataset is available at https://github.com/liaopeiyuan/artbench under a Fair Use license.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. When Style Similarity Scores Fail: Diagnosing Raw CSD Cosine in Artist-Style Evaluation

    cs.CV 2026-05 conditional novelty 7.0 of 10

    Raw CSD cosine similarity produces negative discrimination gaps for many artists and does not support absolute style-fidelity interpretation, but CSLS readout on frozen backbones reduces failures and improves AUC.

  2. DODA: A Database of Datasets for Aesthetics Research

    cs.CV 2026-07 conditional novelty 6.0 of 10

    DODA is a curated online catalog with metadata and precomputed image statistics for over 120 aesthetics-rated image datasets.

  3. FrED: External Data Influence Estimation via Domain Knowledge Graph Grounding

    cs.AI 2026-05 conditional novelty 5.0 of 10

    FrED attributes generated images and forecasts to training samples by multiplying latent similarity with a knowledge-graph rank boost, reporting LDS gains over black-box baselines on ArtBench.

  4. StyleSentinel: Reliable Artistic Copyright Verification via Stylistic Fingerprints

    cs.CV 2025-08 conditional novelty 5.0 of 10

    StyleSentinel detects style mimicry by learning a hypersphere around an artist's style fingerprint in VGG feature space and checking whether suspect images fall inside it.

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