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Deepfake Detection using TCN and EfficientNet-B3

Author(s) Dr. S. Geetha, Vivek Gurudutt K, Vishal S Murali, Pavan T S
Country India
Abstract The increasing computational capabilities ofmodern systems have significantly enhanced deep learningalgorithms, making it easier to create highly realistic, AI-generated videos, commonly known as deepfakes. Thesesynthetic videos, which seamlessly replicate humanappearances, pose serious threats, including politicalmanipulation, fabricated terrorist events, revengepornography, and blackmail. In this study, we propose anovel deep learning-based approach for effectivelydistinguishing between authentic and AI-generated fakevideos. Our method is designed to identify both facereplacement and reenactment deepfakes. Leveraging thepower of Artificial Intelligence (AI) to counter the misuse ofAI, our system utilizes an EfficientNet convolutional neuralnetwork to extract frame-level features. These features aresubsequently used to train a Temporal ConvolutionalNetwork (TCN) to classify videos as either real ormanipulated. To ensure robust evaluation and emulate real-world scenarios, we employ the well-known DeepfakeDetection Challenge[1] dataset for training and testing. Ourproposed system aims to achieve competitive results througha simple yet effective approach.
Keywords Deepfake Detection, Deep Learning, AI- generated Videos, EfficientNet, Temporal Convolutional Network, Frame-level Features, Face Replacement, Face Reenactment, Deepfake Detection Challenge, Generative Adversarial Networks, Autoencoders, Social Media Misinformation, Digital Video Manipulation, Artificial Intelligence, Convolutional Neural Networks, Long Short-Term Memory, Blinking Patterns, Generative Characteristics, Convolutional Traces, Capsule Networks, Multimodal Detection, Visual Analysis, Auditory Analysis, Mel- spectrograms, Synthetic Media
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-04-21
Cite This Deepfake Detection using TCN and EfficientNet-B3 - Dr. S. Geetha, Vivek Gurudutt K, Vishal S Murali, Pavan T S - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.3646
DOI https://doi.org/10.71097/IJSAT.v16.i2.3646
Short DOI https://doi.org/g9gdts
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