Those wizards at Dartmouth’s Computer Science Department have come up with a clever technique for automatically detecting forged JPEG images.
To quote from the abstract:
We describe an efficient technique that automatically detects duplicated regions in a digital image. This technique works by first applying a principal component analysis to small fixed-size image blocks to yield a reduced dimension representation. This representation is robust to minor variations in the image due to additive noise or lossy compression. Duplicated regions are then detected by lexicographically sorting all of the image blocks. We show the efficacy of this technique on credible forgeries, and quantify its robustness and sensitivity to additive noise and lossy JPEG compression.
The dark secret behind those cute AI-generated animal images
Google Brain has revealed its own image-making AI, called Imagen. But don't expect to see anything that isn't wholesome.
The hype around DeepMind’s new AI model misses what’s actually cool about it
Some worry that the chatter about these tools is doing the whole field a disservice.
The walls are closing in on Clearview AI
The controversial face recognition company was just fined $10 million for scraping UK faces from the web. That might not be the end of it.
This horse-riding astronaut is a milestone in AI’s journey to make sense of the world
OpenAI’s latest picture-making AI is amazing—but raises questions about what we mean by intelligence.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.