Is this real?
Substantial Evidence of Manipulation
TrueMedia.org verdict: substantial evidence of manipulation.
Verified by human analyst
Analysis
Results
Generative AI
Detects signatures of GenAI tools
Substantial Evidence
Visual Noise
Variations in pixels and color
Uncertain
Disclaimer: TrueMedia.org uses both leading vendors and state-of-the-art academic AI methods. However, errors can occur.
AI-Generated Insights
Our detector analyzed the media for signs of digital manipulation and noted the following insights. This AI-generated explanation is provided for additional context and is only one component of our analysis.
The image shows clear signs of AI generation and digital manipulation, such as inconsistencies in facial features, lighting, and the overall surreal appearance of the subjects. In particular, there are noticeable issues with the resemblance and proportions of the people, which are common indicators of AI-generated images.
Generative AI5
Detects signatures of GenAI tools
Substantial Evidence
Multi-Modal AI
Analyzes the image for indications it was generated by AI or otherwise digitally manipulated.
Substantial Evidence
99% confidence AI Generated Image Detection
MidJourney
Likely source
The model was trained on a large dataset comprising millions of artificially generated images and human-created images such as photographs, digital and traditional art, and memes sourced from across the web.
Substantial Evidence
93% confidence Universal Fake Detector Analysis
Using the feature space of a large, pretrained vision-language model, this model analyzes images to determine if they were generated by a variety of popular generative and autoregressive models.
Little Evidence
9% confidence Image Generator Analysis
Analyzes image for indications that it was generated by popular AI image generators, like MidJourney, Dall-E, Stable Diffusion and thispersondoesnotexist.com.
Little Evidence
AI Generated Image Detection
Detects AI-generated photo-realistic images, created for example by Generative Adversarial Networks and Diffusion Models like Stable Diffusion, MidJourney, DALL·E 2 and others.
Visual Noise1
Variations in pixels and color
Substantial Evidence
93% confidence Diffusion-Generated Image Detection
Evaluates the discrepancy between the original image and the version reconstructed by pre-trained diffusion models. Such models are known to potentially capture visual noise, commonly associated with the diffusion process.
