AI Video Detector
The rapid adoption of generative AI has made video authenticity harder to assess. Our AI Video Detector helps analyze video content for patterns commonly observed in AI-generated or manipulated media.
Upload a video to receive a likelihood-based assessment, designed for journalism, trust & safety, and compliance workflows.
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MP4, MOV, AVI (Max 1GB)
Upload FileAn AI Video Detector analyzes video footage for visual and temporal indicators that are commonly observed in AI-generated or manipulated content.
How does AI video detection work?
AI video detection generally relies on analyzing visual and temporal patterns across video frames. This AI Video Detector identifies indicators commonly associated with synthetic media.
Identifying synthetic noise patterns and pixel-level discrepancies associated with manipulated videos.
Analyzing frame-to-frame stability and temporal inconsistencies often reported in AI-generated video.
Video analysis layers
Frame-to-frame consistency
Checking for unnatural shifts, jitter, or inconsistent details (e.g., changing accessories or background elements) between consecutive frames.
Motion and physics coherence
Identifying motion behaviors that appear physically implausible or inconsistent with real-world capture.
Compression and rendering artifacts
Distinguishing between standard video compression artifacts and the specific patterns commonly observed in neural network generation.
Indicators commonly associated with manipulated videos
Specific checks for face-swap boundaries, unnatural blinking patterns, and facial landmark inconsistencies typical of synthetic videos.
When should you verify video authenticity?
Frequently Asked Questions AI Video Detector
AI video detection generally relies on analyzing visual and temporal patterns across video frames. This detector applies a multi-stage analysis to identify indicators commonly associated with synthetic media.
The analysis of AI-generated video focuses on identifying universal generative traits rather than searching for specific model signatures. This approach allows the engine to detect patterns across various generation architectures.
Analysis usually completes within a short time, depending on video length and complexity. This frame-by-frame inspection ensures a thorough assessment of technical indicators.
No tool can guarantee absolute certainty. Detection systems provide a probabilistic assessment based on technical indicators to support human verification in determining authenticity.
Data privacy is a priority. Videos are processed securely within the analysis pipeline and are managed according to strict privacy standards without being used for external model training.
Analyze video content for authenticity markers using our advanced likelihood-based assessment.