We present an interactive system that allows the user to manipulate visual content in a natural and realistic way. Without artistic skills, image editing can be a difficult task, even with the best software. It's easy to mess up and make the output look completely unrealistic. Our system attempts to guard against this, keeping the image natural as it is being edited by the user. With our intuitive interface, the user can simply sketch the shape of the handbag in her mind, and our system is able to automatically adjust the handbag, keeping all edits as realistic as possible. A user can further drag the slider to see all the intermediate results and choose the one she likes. We propose to use the generative adversarial networks again to keep image editing within the natural image manifold. Here is an overview of our system. We first protect the original photo onto a low-dimensional latent representation by regenerating it using GAN. We can use various brush tools to modify the color and shape of the generated image. Finally, we apply the same modifications to the original photo to achieve the final result. Here is our interface based on this idea. On the top left, we show the current edited photo. On the bottom left, we provide three brush tools to edit the photo in different aspects, coloring brush for changing the color for a specific region, sketching brush for outlining the shape, and a warping brush for modifying the shape more explicitly. On the right, we show the images in our embedding space generated by the generative adversarial network. Now let's try out these tools. Suppose you're looking for shoes and you found one that almost suits you, but you would like it to be a bit slimmer. You can simply use our warping tool to drag down the shoe tongue. A user can then adjust the slider to see shoes with different degrees of slimness. Now the color seems somewhat boring. Let's make it exciting by adding some color strokes. What happens if there is no image to begin with? And all we have are the user's brush strokes. Our interface can also be used to create new images that best satisfy the user edits. Here is our interface for image generation. The window on the left shows the generated image that best fits the user's edits. The display on the right is showing thumbnails of other modes that fit the edits. Let's draw an outdoor scene. We first create grassland by painting something greenish in the bottom. We can see different samples all with grassland. Let's sketch a mountain. Let's add some blue sky. And finally, let's put some snow in the mountain for a perfect scene. We can use our drawing interface to design products as well. The user sketches some desired shape. Now we can browse different shoes with the same shape but different color and texture. How about a shoe with a red vamp and white outsole? Finally, we can add fine details like shoe laces with our sketching tool. In our editing process, the sequence of intermediate generated images can be seen as a new kind of image morphing. We call it generative transformation. We use the sequence to transform the shape and color of one image to look like another image completely automatically. Here the source on the left is transformed to have the same shape and color as the target image on the right and then transformed back. We compare our morphing results to the optical flow-based interpolation method implemented in Adobe Premiere Pro. We can see our method produces smoother transitions between two images with less solid effects. Thank you for watching. For more information, please visit our project website.