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Found 4 papers, 1 papers with code
ICON$^2$: Reliably Benchmarking Predictive Inequity in Object Detection
As computer vision systems are being increasingly deployed at scale in high-stakes applications like autonomous driving, concerns about social bias in these systems are rising.
Mitigating Bias in Visual Transformers via Targeted Alignment
We visualize the feature space of the transformer self-attention modules and discover that a significant portion of the bias is encoded in the query matrix.
Exploring the Sim2Real Gap Using Digital Twins
An emerging alternative is to use synthetic data, but if the synthetic data is not similar enough to the real data, the performance is typically below that of training with real data.
UDIS: Unsupervised Discovery of Bias in Deep Visual Recognition Models
Deep learning models have been shown to learn spurious correlations from data that sometimes lead to systematic failures for certain subpopulations.
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