2 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
MixFlow: Mixed Source Distributions Improve Rectified Flows
Nazir Nayal, Christopher Wewer, Jan Eric Lenssen
Diffusion models and their variations, such as rectified flows, generate diverse and high-quality images, but they are still hindered by slow iterative sampling caused by the highl…
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…
RbA: Segmenting Unknown Regions Rejected by All
Nazir Nayal, Mısra Yavuz, João F. Henriques +1
Standard semantic segmentation models owe their success to curated datasets with a fixed set of semantic categories, without contemplating the possibility of identifying unknown ob…