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01JamalLee /Omni-Fake-SET Omni-Fake-SET Omni-Fake-SET is the in-distribution split of Omni-Fake, a unified multimodal deepfake dataset for social-media forensics. It covers image, audio, video, and audio–video talking-head (AV-TH) modalities. Each modality uses the same three-way label space: real, fully synthetic, and tampered. Pair with the held-out benchmark Omni-Fake-OOD for out-of-distribution evaluation. Paper: arXiv:2605.01638 Project page: Omni-Fake License: CC-BY-4.0 Video (hybrid… See the full description on the dataset page: https://huggingface.co/datasets/JamalLee/Omni-Fake-SET.audioimage-classification1M<n<10M5 likes2.9k downloads3mo agoHugging Face02nyuuzyou /OpenGameArt-CC-BY-SA-3.0 Dataset Card for OpenGameArt-CC-BY-SA-3.0 Dataset Summary This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the Creative Commons Attribution-ShareAlike 3.0 Unported (CC-BY-SA-3.0) license. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and documents along with their associated metadata. Languages The dataset is primarily… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-CC-BY-SA-3.0.audioimage-classification1K<n<10K1 likes582 downloads1y agoHugging Face03Skhaled /Ar-MUSA Data Directory Structure The Ar-MUSA directory contains annotated datasets organized by batches and annotation teams. Each batch is labeled with a number, and the annotation team is indicated by a letter. The structure is as follows: Ar-MUSA ├── Annotation 1a │ ├── frames # Contains the extracted frames for each record │ ├── audios # Contains the corresponding audio files │ ├── transcripts # Contains the transcripts of the audio files │ └── annotations.csv #… See the full description on the dataset page: https://huggingface.co/datasets/Skhaled/Ar-MUSA.audiotext-classification1K<n<10K3 likes416 downloads1y agoHugging Face04anyangsong /Blockchain-Sensitive-Detect-Datagated Blockchain-Sensitive-Detect-Data English README 复旦大学附属儿科医院-区块链敏感信息检测项目的多模态完整测试数据集。 项目仓库:https://github.com/anyangsong/Blockchain-Sensitive-Detect 数据集:https://huggingface.co/datasets/anyangsong/Blockchain-Sensitive-Detect-Data checkpoints:https://huggingface.co/anyangsong/Blockchain-Sensitive-Detect-Checkpoints 数据以原始文件夹组织,覆盖文本、音频、图像与视频等样本。 该仓库不提供统一的 CSV、Parquet 或 JSONL 清单;类别信息主要由目录名和文件名携带。 内容警告: 数据集包含辱骂、性内容、暴力、政治相关内容、误导性医疗信息、欺诈信息。使用者应仅在具备适当访问控制、伦理审查和当地法律依据的环境中处理这些内容。… See the full description on the dataset page: https://huggingface.co/datasets/anyangsong/Blockchain-Sensitive-Detect-Data.audiotext-classificationn<1K0 likes256 downloads20d agoHugging Face05nyuuzyou /OpenGameArt-CC-BY-SA-4.0 Dataset Card for OpenGameArt-CC-BY-SA-4.0 Dataset Summary This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the Creative Commons Attribution-ShareAlike 4.0 International (CC-BY-SA-4.0) license. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and documents along with their associated metadata. Languages The dataset is primarily… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-CC-BY-SA-4.0.audioimage-classificationn<1K0 likes84 downloads1y agoHugging Face06karankhatavkar /ak47-acoustic-rul-simulated AK-47 Acoustic Run-to-Failure (RUL) Simulation Dataset A synthetic Run-to-Failure dataset for Remaining Useful Life (RUL) estimation of an AK-47's recoil spring from gunshot audio. Because real run-to-failure recordings of a wearing firearm are practically impossible to collect, this dataset is generated by a physics-based Digital Twin that takes a small set of real, healthy gunshot recordings and mathematically simulates the acoustic signature of mechanical wear over thousands… See the full description on the dataset page: https://huggingface.co/datasets/karankhatavkar/ak47-acoustic-rul-simulated.audioaudio-classification1 likes23 downloads4mo agoHugging Face

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