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09/20/2023
You can have your ensemble and run it too – Deep Ensembles Spread Over Time
Ensembles of independently trained deep neural networks yield uncertaint...
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06/01/2023
Hinge-Wasserstein: Mitigating Overconfidence in Regression by Classification
Modern deep neural networks are prone to being overconfident despite the...
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01/21/2023
Raw or Cooked? Object Detection on RAW Images
Images fed to a deep neural network have in general undergone several ha...
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12/07/2022
Towards Explainable Motion Prediction using Heterogeneous Graph Representations
Motion prediction systems aim to capture the future behavior of traffic ...
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10/28/2022
Towards Trustworthy Multi-Modal Motion Prediction: Evaluation and Interpretability
Predicting the motion of other road agents enables autonomous vehicles t...
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04/21/2022
Learning Future Object Prediction with a Spatiotemporal Detection Transformer
We explore future object prediction – a challenging problem where all ob...
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10/07/2021
Dense Gaussian Processes for Few-Shot Segmentation
Few-shot segmentation is a challenging dense prediction task, which enta...
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03/30/2021
Deep Gaussian Processes for Few-Shot Segmentation
Few-shot segmentation is a challenging task, requiring the extraction of...
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12/07/2020
Learning Video Instance Segmentation with Recurrent Graph Neural Networks
Most existing approaches to video instance segmentation comprise multipl...
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11/28/2018
A Generative Appearance Model for End-to-end Video Object Segmentation
One of the fundamental challenges in video object segmentation is to fin...
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04/18/2018
Unveiling the Power of Deep Tracking
In the field of generic object tracking numerous attempts have been made...
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06/09/2017