Image Editing without Typing

Text-guided Image Editing (TIE) uses a typing box to replace the button-driven interfaces in traditional software such as Adobe Photoshop, offering remarkable convenience. However, it suffers from a critical limitation: on mobile devices, the virtual keyboard occupies nearly half of the screen, which occludes or resizes the image to be edited and deteriorates user experience. We propose a potential new framework: the text box is directly eliminated, and users express all editing requirements by drawing or writing on the image with a virtual pen. We present the Jasmine Project, involving: (1) a new task NoTIE: No-Typing Image Editing. We define 14 subtasks, and conduct a user survey to identify how users express editing demands using the virtual pen; (2) a new dataset Jasmine-Dataset-15K: a high-quality 2K-resolution dataset, strictly filtered by real humans with a 50.4% high discard rate, with Style Change subtask samples exclusively reviewed by art-major students; (3) a new benchmark Jasmine-Benchmark-1K: 1,381 high-quality human-selected samples, equipped with an MLLM-as-a-Judge evaluation pipeline. We benchmark 19 SOTA models and our 3 models. All evaluation prompts are twice the length of the previous TIE work, and all scoring criteria are derived from the first-hand feedback during the human filtering process; (4) a new model series Jasmine-Model-Family: a Thinker-Editor architecture that outperforms all open-source models and ByteDance's Seedream series. We hope this work can make image editing more convenient on mobile devices, and we call for community help to extend this work.