 Dear Fellow Scholars, this is 2 Minute Papers with Karo Zonai-Fehir. The title of this paper is very descriptive, it says, controllable characters extracted from real-world videos. This sounds a little like science fiction, so let's pick this apart. If we forget about the controllable part, we get something that you've seen in this series many times, pose estimation. Pose estimation means that we have a human character in an image or a video, have a computer program look at it and tell us the current position this character is taking. This is useful for medical applications such as detecting issues with motor functionality, fall detection, or we can also use it for motion capture for our video games and blockbuster movies. So just performing the pose estimation part is a great invention, but relatively old news. So what's really new here? Why is this work interesting? How does it go beyond pose estimation? Well, as a hint, the title contains an additional word controllable. So look at this. Woohoo! As you see, this technique is not only able to identify where a character is, but we can grab a controller and move it around. This means making this character perform novel actions and showing it from novel views. It's really remarkable because this requires a proper understanding of the video we are watching. And this means that we can not only watch these real world videos, as you see this small piece of footage used for the learning, but by performing these actions with the controller, we can make a video game out of it. Especially given that here, the background has also been changed. To achieve this, this work contains two key elements. Element number one is the pose-to-pose network that takes an input posture and the button we pushed on the controller and creates the next step of the animation. And then, element number two, the post-of-frame architecture blends this new animation step into an already existing image. The neural network that performs this is trained in a way where it is encouraged to create these character masks in a way that is continuous and doesn't contain jarring jumps between the individual frames leading to smooth and believable movements. Now clearly, anyone who takes a cursory look sees that the animations are not perfect and still contain artifacts, but just imagine that this paper is among the first introductory works on this problem. Just imagine what will have two more papers down the line. I can't wait. Thanks for watching and for your generous support and I'll see you next time.