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cs.CV2024
Mitigating Distributional Shift in Semantic Segmentation via Uncertainty Estimation from Unlabelled Data
David S. W. Williams, Daniele De Martini, Matthew Gadd +1
Knowing when a trained segmentation model is encountering data that is different to its training data is important. Understanding and mitigating the effects of this play an importa…
cs.CV2024
Masked Gamma-SSL: Learning Uncertainty Estimation via Masked Image Modeling
David S. W. Williams, Matthew Gadd, Paul Newman +1
This work proposes a semantic segmentation network that produces high-quality uncertainty estimates in a single forward pass. We exploit general representations from foundation mod…
cs.CV2021
Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning
David Williams, Matthew Gadd, Daniele De Martini +1
In this work, we train a network to simultaneously perform segmentation and pixel-wise Out-of-Distribution (OoD) detection, such that the segmentation of unknown regions of scenes…