An explainable deepfake detection framework on a novel unconstrained dataset

Abstract In this work, we created a new large-scale unconstrained high-quality Deepfake Image (DFIM-HQ) dataset containing 140K images. Compared to existing datasets, this dataset includes a variety of diverse scenarios, pose variations, high-quality degradations, and illumination variations, making...

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Номзүйн дэлгэрэнгүй

Үндсэн зохиолчид:	Sherin Mathews, Shivangee Trivedi, Amanda House, Steve Povolny, Celeste Fralick
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	Springer 2023-01-01
Цуврал:	Complex & Intelligent Systems
Нөхцлүүд:	Deepfakes Deepfake image detection techniques Digital media forensics Deep learning Explainability AI bias
Онлайн хандалт:	https://doi.org/10.1007/s40747-022-00956-7
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!