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
Little Evidence
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 appears to have been digitally manipulated based on the unusual appearance of the individual on the left, especially the face, which does not blend naturally with the surrounding environment. This suggests that the image may have been altered or generated by AI tools.
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
100% 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
96% confidence Image Generator Analysis
MidJourney
Likely source
Analyzes image for indications that it was generated by popular AI image generators, like MidJourney, Dall-E, Stable Diffusion and thispersondoesnotexist.com.
Substantial Evidence
76% 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.
Substantial Evidence
74% confidence 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
Little Evidence
28% 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.
