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Found 3 papers, 1 papers with code
GELDA: A generative language annotation framework to reveal visual biases in datasets
Results on real datasets show that GELDA can generate accurate and diverse visual attribute suggestions, and uncover biases such as confounding between class labels and background features.
F?D: On understanding the role of deep feature spaces on face generation evaluation
Moreover, FD using features from a face gender classifier emphasize hair length more than distances in an identity (recognition) feature space.
Deep object detection for waterbird monitoring using aerial imagery
In this work, we present a deep learning pipeline that can be used to precisely detect, count, and monitor waterbirds using aerial imagery collected by a commercial drone.
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