Summary of Semi-supervised Coupled Thin-plate Spline Model For Rotation Correction and Beyond, by Lang Nie et al.
Semi-Supervised Coupled Thin-Plate Spline Model for Rotation Correction and Beyond
by Lang Nie, Chunyu Lin, Kang Liao, Shuaicheng Liu, Yao Zhao
First submitted to arxiv on: 24 Jan 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 proposed CoupledTPS model leverages thin-plate spline (TPS) transformations to achieve flexible and powerful warping in single-image-based tasks like rotation correction, rectangling, and portrait correction. By iteratively coupling multiple TPS with limited control points, the model breaks the bottleneck of content distortion. An iterative search predicts new control points based on current latent conditions, while a warping flow bridges different TPS transformations to eliminate interpolation errors. A semi-supervised learning scheme is developed to improve warping quality by exploiting unlabeled data and its graphic augmentation. The code and data are available at https://github.com/nie-lang/CoupledTPS. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary CoupledTPS is a new way to correct images using computer algorithms. It takes thin-plate spline (TPS) transformations, which can stretch or shrink images in different ways, and makes them more powerful by combining multiple TPS transformations together. This helps fix issues with image distortion. The model also uses unlabeled data to improve the quality of the corrections. |
Keywords
* Artificial intelligence * Semi supervised
