A few years ago I wrote about the upcoming shift from canvas-centric image and video editing tools to object-centric ones. At the time it was mostly early demos and research projects hinting at what object-centric editing interfaces could be. Reve's new layout model makes them real.
Digital image editing has always been canvas-centric. In Photoshop (used by something like 90% of creative professionals) you're adding, removing, or changing pixels. The application doesn't really know what it's looking at because there's no semantic understanding of the subject matter baked in. It's just pixels and, therefore, lots of pixel manipulation tools.
When every object in an image is identified and addressable, you can edit by changing the subject itself. Move the cat here. Make it a sunny day. Make the cat's eyes green. Popular tools like Photoshop were built before these kinds of capabilities existed so they put pixel manipulation front and center instead of behind the scenes. Object-centric editing flips this.
Large Layout Models
Most image models use text as their internal representation: a language model expands your prompt into a long description, and a diffusion model renders that into pixels. Text can say a lot, but it says it loosely, and loose input means loose control. To see that in action, just tweak a prompt and watch the whole image change.
Reve's new model is trained to think in layouts instead of prose. A layout is a structured, hierarchical description of an image where every element has a location, a size, a description, and attributes like color. The model takes layouts, instructions, and images as input, works out a layout in its thinking, and then renders the pixels. Layout is to an image what HTML is to a webpage.
When every image is built from a layout, all the elements in it are addressable. A designer can change the color of a car without regenerating the whole image. An interior decorator can move chairs around a room. Shadows, reflections, and perspective stay coherent because the model understands how the pieces relate, not just which colors land where on a canvas.
Because a layout is a readable, structured format, it can also be it a shared interface between people and AI agents. A agent can reason about a layout the way it reasons about code. That enables new forms of human machine collaboration that canvas-centric approaches can't. And we'll see a lot of new creative tools as a result.