Deepfakes-QA-15K

# **Deepfake Quality Assessment** Deepfake QA is a Deepfake Quality Assessment model designed to analyze the quality of deepfake images & videos. It evaluates whether a deepfake is of good or bad quality, where: - **0** represents a bad-quality deepfake - **1** represents a good-quality deepfake This classification serves as the foundation for training models on deepfake quality assessment, helping improve deepfake detection and enhancement techniques. ## Citation If you use our dataset or models, please cite: ```bibtex @misc{deepfake_quality_assessment_2025, author = {Wildy AI Team Collaborations}, title = {Deepfake Quality Assessment Models}, year = {2025}, note = {Early release}, models_training = {@prithivMLmods}, dataset_curation_strategy = {@prithivMLmods}, dataset_curation = {Wildy AI Team} } ```# **深度伪造质量评估（Deepfake Quality Assessment）** 深度伪造质量评估模型（简称Deepfake QA）是一款专为分析深度伪造图像与视频质量而研发的模型，核心任务为判别深度伪造内容的质量优劣，具体标注规则如下： - **0** 代表劣质深度伪造内容 - **1** 代表优质深度伪造内容 该分类任务可作为深度伪造质量评估模型训练的核心支撑，助力优化深度伪造检测与增强相关技术。 ## 引用 若您使用本数据集或模型，请引用如下： bibtex @misc{deepfake_quality_assessment_2025, author = {Wildy AI Team Collaborations}, title = {Deepfake Quality Assessment Models}, year = {2025}, note = {早期发布版本}, models_training = {@prithivMLmods}, dataset_curation_strategy = {@prithivMLmods}, dataset_curation = {Wildy AI Team} }

搜集汇总

背景与挑战

背景概述

Deepfakes-QA-15K是一个用于深度伪造质量评估的数据集，通过二分类（0表示低质量，1表示高质量）来支持模型训练，旨在改进深度伪造的检测和增强技术。该数据集基于Apache License 2.0许可证发布，大小为6.60GB，于2025年2月更新。