1 citations · 1 across the 5 of their papers we have counts for
5 papers
FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow
Sadra Safadoust, Fabio Tosi, Matteo Poggi +1
We present FlowIt, a novel architecture for optical flow estimation that combines global matching with confidence and occlusion-guided refinement. At its core, FlowIt leverages a h…
Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratios
Youssef Shoeb, Nazir Nayal, Azarm Nowzad +2
Detecting road obstacles is essential for autonomous vehicles to navigate dynamic and complex traffic environments safely. Current road obstacle detection methods typically assign…
A Likelihood Ratio-Based Approach to Segmenting Unknown Objects
Nazir Nayal, Youssef Shoeb, Fatma Güney
Addressing the Out-of-Distribution (OoD) segmentation task is a prerequisite for perception systems operating in an open-world environment. Large foundational models are frequently…
CarFormer: Self-Driving with Learned Object-Centric Representations
Shadi Hamdan, Fatma Güney
The choice of representation plays a key role in self-driving. Bird's eye view (BEV) representations have shown remarkable performance in recent years. In this paper, we propose to…
Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes
Youssef Shoeb, Robin Chan, Gesina Schwalbe +3
In the life cycle of highly automated systems operating in an open and dynamic environment, the ability to adjust to emerging challenges is crucial. For systems integrating data-dr…