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cs.CV2024★ 1 cited
DIAGen: Semantically Diverse Image Augmentation with Generative Models for Few-Shot Learning
Tobias Lingenberg, Markus Reuter, Gopika Sudhakaran +3
Simple data augmentation techniques, such as rotations and flips, are widely used to enhance the generalization power of computer vision models. However, these techniques often fai…
cs.LG2024
DeiSAM: Segment Anything with Deictic Prompting
Hikaru Shindo, Manuel Brack, Gopika Sudhakaran +3
Large-scale, pre-trained neural networks have demonstrated strong capabilities in various tasks, including zero-shot image segmentation. To identify concrete objects in complex sce…