562 citations · 576 across the 6 of their papers we have counts for
4 papers
Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies
Laura Gustafson, Megan Richards, Melissa Hall +3
Despite impressive advances in object-recognition, deep learning systems' performance degrades significantly across geographies and lower income levels raising pressing concerns of…
Segment Anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi +9
We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest seg…
Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers
Melissa Hall, Bobbie Chern, Laura Gustafson +4
Disaggregated performance metrics across demographic groups are a hallmark of fairness assessments in computer vision. These metrics successfully incentivized performance improveme…
Revisiting Weakly Supervised Pre-Training of Visual Perception Models
Mannat Singh, Laura Gustafson, Aaron Adcock +7
Model pre-training is a cornerstone of modern visual recognition systems. Although fully supervised pre-training on datasets like ImageNet is still the de-facto standard, recent st…