Masking Strategies for Background Bias Removal in Computer Vision Models

1 code implementation • 23 Aug 2023 • Ananthu Aniraj, Cassio F. Dantas, Dino Ienco, Diego Marcos

Models for fine-grained image classification tasks, where the difference between some classes can be extremely subtle and the number of samples per class tends to be low, are particularly prone to picking up background-related biases and demand robust methods to handle potential examples with out-of-distribution (OOD) backgrounds.

Fine-Grained Image Classification