CaricatureBooth: Data-Free Interactive Caricature Generation in a Photo Booth

Zhiyu Qu, Yunqi Miao, Zhensong Zhang, Jifei Song, Jiankang Deng, Yi-Zhe Song; Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR), 2025, pp. 10815-10824

We present CaricatureBooth, a system that transforms caricature creation into a simple interactive experience -- as easy as using a photo booth! A key challenge in caricature generation is two-fold: the scarcity of high-quality caricature data and the difficulty in enabling precise creative control over the exaggeration process while maintaining identity. Prior approaches either require large-scale caricature and photo data or lack intuitive mechanisms for users to guide the deformation without losing identity. We address the data scarcity by synthesising training data through Thin Plate Spline (TPS) deformation of standard face images. For creative control, we design a Bezier curve interface where users can easily manipulate facial features, with these edits then driving TPS transformations at inference time. When combined with a pre-trained ID-preserving diffusion model, our system maintains both identity preservation and creative flexibility. Through extensive experiments, we demonstrate that CaricatureBooth achieves state-of-the-art quality while making the joy of caricature creation as accessible as taking a photo -- just walk in and walk out with your personalised caricature! Code is available at https://github.com/WinKawaks/CaricatureBooth.