7 citations · 12 across the 14 of their papers we have counts for
21 papers · 1 filter
ShapeAug++: More Realistic Shape Augmentation for Event Data
Katharina Bendig, René Schuster, Didier Stricker
The novel Dynamic Vision Sensors (DVSs) gained a great amount of attention recently as they are superior compared to RGB cameras in terms of latency, dynamic range and energy consu…
Object Permanence in Object Detection Leveraging Temporal Priors at Inference Time
Michael Fürst, Priyash Bhugra, René Schuster +1
Object permanence is the concept that objects do not suddenly disappear in the physical world. Humans understand this concept at young ages and know that another person is still th…
Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation
Dipam Goswami, René Schuster, Joost van de Weijer +1
In class-incremental semantic segmentation (CISS), deep learning architectures suffer from the critical problems of catastrophic forgetting and semantic background shift. Although…
RMS-FlowNet: Efficient and Robust Multi-Scale Scene Flow Estimation for Large-Scale Point Clouds
Ramy Battrawy, René Schuster, Mohammad-Ali Nikouei Mahani +1
The proposed RMS-FlowNet is a novel end-to-end learning-based architecture for accurate and efficient scene flow estimation which can operate on point clouds of high density. For h…
Multi-scale Iterative Residuals for Fast and Scalable Stereo Matching
Kumail Raza, René Schuster, Didier Stricker
Despite the remarkable progress of deep learning in stereo matching, there exists a gap in accuracy between real-time models and slower state-of-the-art models which are suitable f…
MonoComb: A Sparse-to-Dense Combination Approach for Monocular Scene Flow
René Schuster, Christian Unger, Didier Stricker
Contrary to the ongoing trend in automotive applications towards usage of more diverse and more sensors, this work tries to solve the complex scene flow problem under a monocular c…