Weakly supervised semantic segmentation (WSSS) approaches typically rely on class
activation maps (CAMs) for initial seed generation, which often fail to capture global context …

Neural networks can learn spurious correlations that lead to the correct prediction in a
validation set, but generalise poorly because the predictions are right for the wrong reason …

Few-shot learning aims to recognize novel concepts by leveraging prior knowledge learned
from a few samples. However, for visually intensive tasks such as few-shot semantic …

Shortcuts, also described as Clever Hans behavior, spurious correlations, or confounders,
present a significant challenge in machine learning and AI, critically affecting model …

Weakly supervised semantic segmentation (WSSS) approaches typically rely on class
activation maps (CAMs) for initial seed generation, which often fail to capture global context …