activity
20202026
most citedRbA: Segmenting Unknown Regions Rejected by All

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

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…

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2022★ 2 cited

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…

cs.DC2020

A containerized proof-of-concept implementation of LightChain system

Yahya Hassanzadeh-Nazarabadi, Nazir Nayal, Shadi Sameh Hamdan +2

LightChain is the first Distributed Hash Table (DHT)-based blockchain with a logarithmic asymptotic message and memory complexity. In this demo paper, we present the software archi…