Toward Robust Visual Recognition System under Group Shifts

Recently, people are making more and more efforts to strive for fairness. While human beings can be a main source of bias, machines can also be biased when generating prediction results. As the frequency of using computers to make decisions, fairness-enhancing techniques have received a lot of attention. Our project focuses on reducing bias generated by image classification algorithms, and thus improve the worst-case performance in image classification.