of literature that has been most explored to gain insight about video classification for deep fake detection was video action recognition [9,10,11,12] because of the extensive development in the field in recent years and similar spatial–temporal processing nature to that of deepfake detection. On...
Deep-Fake is an emerging technology used in synthetic media which manipulates individuals in existing images and videos with someone elses likeness. This paper presents the comparative study of different deep neural networks employed for Deep-Fake video detection. In the model, the features from the...
Combining ResNet50 and LSTM can help to leverage the strengths of both architectures and improve the accuracy of deep fake video detection, especially for videos that involve both image-based and sequential data. A comparative analysis of different models were assessed using various datasets such ...
5.2、Fake Video Detection 大多数图像检测方法不能用于视频,因为视频压缩后帧数据会严重退化。视频具有在帧组之间变化的时间特性,对于设计为仅检测静态图像的方法具有挑战性。 使用跨视频帧的时间模式的方法主要基于深度递归网络模型来检测deepfake视频,可分为两类:采用时间特征的方法和探索帧内视觉伪影的方法。 图5-1...
[1] ProtectingWorld Leaders Against Deep Fakes【CVPR 2019】 [2] Detecting Deep-Fake Videos from Appearance and Behavior【WIFS 2020】 [3] ID-Reveal: Identity-aware DeepFake Video Detection【ICCV 2021】 [4] Audio-Visual Person-of-Interest DeepFake Detection【arxiv】 Supervised Learning [5] Freque...
Deepfakes allow for the automated gen- eration of fake video content, often accomplished through the use of generative adversarial networks. To address the increasing issue of deepfakes, this study focuses on constructing a model that incorporates advanced techniques. The researchers combined the ResNe...
随着伪造音频数据集的出现，多模态检测成为新挑战。例如，[4]结合音频信息，利用对比学习技术判断视频和音频的嵌入距离，识别特定对象的伪造视频。同时，[3]运用3DMM特征和metric learning的Temporal ID Network，通过生成网络生成假特征，进行GAN训练，实现了对视频真伪的判断。在数据集方面，例如[3]利用...
【3.2 – Fake Video Detection】 大多数图像检测方法不能用于视频,因为视频压缩后帧数据会严重退化[73]。 此外,视频具有在帧组之间变化的时间特性,因此对于设计为仅检测静态图像的方法具有挑战性。 本小节重点介绍Deepfake视频检测方法,并将其分为两类:采用时间特征的方法和探索帧内视觉伪像的方法 ...
3.2 Fake Video Detection 由于视频压缩后帧数据的严重退化,大多数图像检测方法不能用于视频检测。此外,视频的时间特征在不同的帧之间是不同的,因此设计方法来检测假视频相对于检测假图像是有挑战性的。本小节重点介绍了deepfake视频检测方法,并将其分为两组:使用时间特征的方法和在帧内检测视觉伪影的方法。 3.2.1 ...
• Accurate deepfake detection: Thanks to sophisticated algorithms, DeepDetekt precisely identifies fake content. • Ease of use: A simple and intuitive interface allows quick analysis of photos and videos. • Offline operation: DeepDetekt does not require a constant internet connection, allowing ...