arxiv V2

arxiv_v2_arXiv/sec/conclusion.tex

@@ -0,0 +1,10 @@
+
+\section{Discussion \& Conclusion}
+\label{sec:conclusion}
+
+We introduce \schemename, a novel data augmentation scheme that facilitates improved Transformer training for image classification.
+By explicitly separating and recombining foreground objects and backgrounds, \schemename enables controlled data augmentation beyond existing image compositions, leading to significant performance gains on ImageNet and downstream fine-grained classification tasks.
+Furthermore, \schemename provides a powerful framework for analyzing model behavior and quantifying biases, including background robustness, foreground focus, center bias, and size bias.
+Our experiments demonstrate that training using \schemename not only boosts accuracy but also significantly reduces these biases, resulting in more robust and generalizable models.
+In the future, we see \schemename be also applied to other datasets and tasks, like video recognition or segmentation.
+\schemename's ability to both improve performance and provide insights into model behavior makes it a valuable tool for advancing CV research and developing more reliable AI systems.