28 citations · 35 across the 3 of their papers we have counts for
6 papers
Multimodal Future Localization and Emergence Prediction for Objects in Egocentric View with a Reachability Prior
Osama Makansi, Özgün Cicek, Kevin Buchicchio +1
In this paper, we investigate the problem of anticipating future dynamics, particularly the future location of other vehicles and pedestrians, in the view of a moving vehicle. We a…
Parting with Illusions about Deep Active Learning
Sudhanshu Mittal, Maxim Tatarchenko, Özgün Çiçek +1
Active learning aims to reduce the high labeling cost involved in training machine learning models on large datasets by efficiently labeling only the most informative samples. Rece…
Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction
Osama Makansi, Eddy Ilg, Özgün Cicek +1
Future prediction is a fundamental principle of intelligence that helps plan actions and avoid possible dangers. As the future is uncertain to a large extent, modeling the uncertai…
Learning Representations for Predicting Future Activities
Mohammadreza Zolfaghari, Özgün Çiçek, Syed Mohsin Ali +3
Foreseeing the future is one of the key factors of intelligence. It involves understanding of the past and current environment as well as decent experience of its possible dynamics…
Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow
Eddy Ilg, Özgün Çiçek, Silvio Galesso +4
Optical flow estimation can be formulated as an end-to-end supervised learning problem, which yields estimates with a superior accuracy-runtime tradeoff compared to alternative met…
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S. Lienkamp +2
This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images. We outline two attractive use cases of this method: (1) In a semi…