Accuracy
Understand when AI video detection is accurate and when it is not. Covers false positives, false negatives, compression, filters, short clips, animated content, and AI-assisted editing.
AI Video Detector is a review tool. Use the verdict, score, confidence band, evidence notes, and source context together before making a decision. A high score means strong AI-generation signals were found — but it does not prove the video is fake. A low score means few signals were found — but it does not prove the video is real.
For a full breakdown of what each field means, see Sample Report.
A false positive occurs when a real video is flagged as likely AI-generated. This can happen when the video was heavily compressed or re-encoded (platform transcoding, messaging app compression), uses beauty filters, skin smoothing, or face-altering effects, is a screen recording of another video, has heavy color grading or post-processing, or is animated, a slideshow, or uses motion graphics.
A false negative occurs when an AI-generated video is not flagged. This can happen when the AI model produces very high-quality output with few detectable artifacts, the video has been post-processed to remove AI signals, the video is very short and provides insufficient signal, the video has been heavily compressed hiding subtle artifacts, or the AI generation was partial (e.g., only the background was AI-generated).
Every re-encoding cycle (upload to platform → download → re-upload) destroys subtle visual signals the detector relies on. Messaging apps (WhatsApp, Telegram) apply especially heavy compression. For best results, upload the original file.
Beauty filters, skin-smoothing effects, and face-altering apps can mimic AI-generation artifacts (unnaturally smooth skin, consistent lighting). They can also mask real AI-generation signals. Videos with heavy filters produce less reliable results.
Videos under 3 seconds provide very few frames for temporal analysis. The scanner needs enough consecutive frames to check motion consistency, object permanence, and physics. Shorter clips may still produce a result, but confidence will be lower.
Screen recordings add compression, resolution loss, and potential UI overlays. Reposts from one platform to another go through re-encoding. Both reduce the quality of evidence available to the detector.
Animated videos, motion graphics, video game footage, and virtual camera renders are synthetic by nature. The detector may flag them as AI-generated even though they were created with traditional animation or game engines. These are not false positives in the technical sense, but they are not the type of AI-generated content most users are looking for.
Many modern videos use AI tools for part of the production — AI upscaling, AI background replacement, AI color grading, or AI noise reduction. The detector may flag partial AI signals without being able to distinguish "fully AI-generated" from "AI-enhanced real footage." This is a fundamental limitation of current detection technology.
For details on how the scanner works, see Methodology.