Summary of Inksight: Offline-to-online Handwriting Conversion by Learning to Read and Write, By Blagoj Mitrevski et al.
InkSight: Offline-to-Online Handwriting Conversion by Learning to Read and Write
by Blagoj Mitrevski, Arina Rak, Julian Schnitzler, Chengkun Li, Andrii Maksai, Jesse Berent, Claudiu Musat
First submitted to arxiv on: 8 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The InkSight system aims to bridge the gap between traditional paper-based note-taking and digital note-taking. By developing a derendering model, it can convert offline handwriting into digital ink (online handwriting) with high accuracy. The proposed approach combines reading and writing priors, allowing for training in the absence of large amounts of paired samples. To our knowledge, this is the first work that effectively derenders handwritten text in arbitrary photos with diverse visual characteristics and backgrounds. The model generalizes beyond its training domain into simple sketches. Human evaluation reveals that 87% of the samples produced by the model are considered valid tracings of the input image, and 67% look like pen trajectories traced by a human. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary InkSight is a system that helps people who take notes by hand to easily turn their work into digital notes. This can be useful because many people prefer writing by hand, but it’s hard to share or edit handwritten notes. The InkSight team created a special model that can understand handwriting and convert it into a digital format. They tested the model on many different types of images and found that it works well even when the handwriting is messy or there are distractions in the background. |
