Somaieh Amraee — accepted AI-conference papers

2026

UniTrack: Differentiable Graph Representation Learning for Multi-Object Tracking

Bishoy Galoaa, Xiangyu Bai, Utsav Nandi, Sai Siddhartha Vivek Dhir Rangoju, Somaieh Amraee, Sarah Ostadabbas

ICLR 2026poster

We present UniTrack, a plug-and-play graph-theoretic loss function designed to significantly enhance multi-object tracking (MOT) performance by directly optimizing tracking-specific objectives through unified differentiable learning. Unlike prior graph-based MOT methods that redesign tracking archit…

Cited by 0 Source ↗code ↗Scholar ↗

2025

More Than Meets the Eye: Enhancing Multi-Object Tracking Even with Prolonged Occlusions

Bishoy Galoaa, Somaieh Amraee, Sarah Ostadabbas

ICML 2025poster

This paper introduces MOTE (MOre Than meets the Eye), a novel multi-object tracking (MOT) algorithm designed to address the challenges of tracking occluded objects. By integrating deformable detection transformers with a custom disocclusion matrix, MOTE significantly enhances the ability to track ob…

Cited by 0 Source ↗PDF ↗Scholar ↗