Abstract: I will introduce “generative re-photography” methods that use new generative video models to get more out of your photos—even the blurry ones. First, I will present a method for converting motion-blurred images to video. This method can even predict the “past” and “future” (right before and after the capture) of a motion-blurred image. I will then show how this method can bring “historical scenes to life” such as photos of soldiers landing on north side of France during the Normandy invasion of 1944 or a boxing match between Mohammed Ali and Jurgen Blin in 1971. Then, I will present a robust post-capture refocusing method that converts a single defocus-blurred image into a focal stack spanning multiple focus distances. Our work overturns the conventional wisdom of photography, suggesting these “corrupted images” can actually reveal more about the world than the “perfect” images which have been the holy grail of image processing. Additionally, our findings suggest that video models implicitly understand how camera capture settings affect image appearance, and I will discuss how this exciting capability could inspire new directions for computational photography.

Bio: Sai Tedla is a PhD student at York University, Toronto, supervised by Michael Brown. He currently works on the intersection of computational photography and generative models. He is a visiting student at the University of Toronto supervised by David Lindell and Kyros Kutulakos, and will soon join the university as a Schmidt AI Postdoctoral Fellow. Additionally, Sai is a current intern at Sony AI Japan and has previously interned at Samsung AI Center Toronto and Adobe NextCam.

Homepage:  https://sites.google.com/view/tedlasai

Sponsor

The VASC seminar is generously sponsored by HeyGen, an all-in-one AI-powered video generation platform that leverages advances in computer vision, generative modeling, and multimodal learning to make high-quality video creation both scalable and accessible.