

Stabledrag
Overview :
StableDrag is a point-based image editing framework designed to address the issues of inaccurate point tracking and incomplete motion supervision in existing drag-and-drop methods. It employs a discriminative point tracking method and a confidence-based latent enhancement strategy. The former accurately localizes updated handle points, improving stability for long-distance operations; the latter ensures that the quality of the optimized latent representation is as high as possible throughout all operational steps. The framework instantiates two image editing models, StableDrag-GAN and StableDrag-Diff, which demonstrate more stable drag performance through extensive qualitative experiments and quantitative evaluations on the DragBench."
Target Users :
Suitable for point-based image editing tasks, such as object removal, insertion, and deformation.
Use Cases
Remove an object from an image through drag-and-drop operations
Insert an object into an image through drag-and-drop operations
Deform the posture of a figure in an image through drag-and-drop operations
Features
Discriminative point tracking method for precise localization of updated points
Confidence-based latent enhancement strategy for optimizing latent representation quality
Instantiation of two models: StableDrag-GAN and StableDrag-Diff
Improved stability for point-based drag-and-drop image editing
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