2023’s annual Computer Vision and Pattern Recognition (CVPR) conference has come to an end, and after returning from Vancouver, we’ve spent the last few days reflecting on what an incredible event it was. With more than 6500 in-person attendees, we were lucky enough to meet some amazing people and gain some insights from leaders in the field of computer vision.
Below, we’re unpacking our top takeaways from the event.
“Attending CVPR was a great experience. I had the opportunity to witness all the cutting-edge research going on in the field of computer vision and engage in interesting discussions with a diverse group of people.” - Shaunagh Downing
“CVPR is a rare opportunity for academia and industry to exchange perspectives – essential for driving ideas forward. The only way we combat emerging online threats is to act as a community, and CVPR is a vital part of making that happen.” - Fred Lichtenstein
AI is evolving, fast
CVPR 2023 was full of high-quality exciting research and provided the perfect opportunity to gain some valuable insight into the current state of the field, to find out what research topics are popular, and to see where the field is going. It is important to stay on top of all the rapidly developing research, both to ensure we are harnessing current tools to the best of our ability, and to assess the potential threats of new technology.
Traditional forensic methods are just as important as ever
How can investigators quickly classify if an image is AI-generated or not?
We were lucky enough to attend some great workshops during our time there, including an insightful media forensics workshop led by Hany Farid (a world-renowned professor in image analysis and digital forensics).
One such school of thought useful for classifying whether an image is AI-generated or not returns to traditional image forensics techniques.
Currently, generative AI, while able to create detailed and complex images, may still make several mistakes – such as creating numerous sources of sunlight in the same image. While returning to traditional analysis techniques may help determine if an image is generated or not for now, there’s no telling how long these techniques will stay relevant. AI-based detectors are another promising option for determining the authenticity of image.
The content authenticity initiative
Image authenticity was a big focus throughout the event. Founded by Adobe, the Content Authenticity Initiative is a worldwide initiative that aims to create a standardised practice of authenticating the source of an image’s creation. This would consist of adding a ‘layer of verifiable trust to all types of digital content’ with a stamp attached to each image showcasing where it originated – whether through photography, digital art, or AI-generated.