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12/20/2022
Weakly supervised training of universal visual concepts for multi-domain semantic segmentation
Deep supervised models have an unprecedented capacity to absorb large qu...
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07/18/2022
Automatic universal taxonomies for multi-domain semantic segmentation
Training semantic segmentation models on multiple datasets has sparked a...
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07/06/2022
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition
Anomaly detection can be conceived either through generative modelling o...
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12/23/2021
Dense anomaly detection by robust learning on synthetic negative data
Standard machine learning is unable to accommodate inputs which do not b...
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08/25/2021
Multi-domain semantic segmentation with overlapping labels
Deep supervised models have an unprecedented capacity to absorb large qu...
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01/22/2021
Dense outlier detection and open-set recognition based on training with noisy negative images
Deep convolutional models often produce inadequate predictions for input...
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11/22/2020
Dense open-set recognition with synthetic outliers generated by Real NVP
Today's deep models are often unable to detect inputs which do not belon...
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09/02/2020
Multi-domain semantic segmentation with pyramidal fusion
We present our submission to the semantic segmentation contest of the Ro...
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08/03/2019
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift
Recent success on realistic road driving datasets has increased interest...
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03/20/2019
In Defense of Pre-trained ImageNet Architectures for Real-time Semantic Segmentation of Road-driving Images
Recent success of semantic segmentation approaches on demanding road dri...
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08/23/2018
Discriminative out-of-distribution detection for semantic segmentation
This paper considers dense detection of out-of-distribution pixels. As a...
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06/09/2018