{
 "id": "deepghs/csip_eval",
 "owner": "deepghs",
 "name": "csip_eval",
 "downloads": 68,
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 "last_modified": "2025-11-17T18:40:40.000Z",
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 "tasks": [
  "zero-shot-image-classification"
 ],
 "citation": "@misc{csip_eval_dataset,\n  title        = {CSIP Evaluation Dataset: Human-Curated Anime Style Images for Zero-Shot Classification},\n  author       = {deepghs},\n  howpublished = {\\url{https://huggingface.co/datasets/deepghs/csip_eval}},\n  year         = {2023},\n  note         = {Human-picked evaluation dataset for anime style classification containing high-quality images from various artists},\n  abstract     = {The CSIP Evaluation Dataset is a human-curated collection of anime-style images specifically designed for evaluating zero-shot image classification models trained on artistic styles. This dataset represents the highest quality subset from the Contrastive anime Style Image Pre-Training (CSIP) project, containing carefully selected images that showcase distinct artistic characteristics from various anime artists. The dataset serves as a benchmark evaluation tool for assessing model performance on style recognition tasks in the anime art domain.},\n  keywords     = {human-curated, zero-shot classification, anime styles, evaluation benchmark, contrastive learning}\n}",
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