activity
20242026
collaborators

10 papers

cs.CV2026

SAGE-OR: Semi-supervised Adaptive Scene Graph Generation for Operating Rooms

Brandon Leblanc, Charalambos Poullis

Current surgical scene graph generation methods depend on dense multi-modal supervision and specialized hardware (synchronized RGB-D sensors, calibration rigs), making dataset cons…

cs.HC2026

Designing Fatigue-Aware VR Interfaces via Biomechanical Models

Harshitha Voleti, Charalambos Poullis

Prolonged mid-air interaction in virtual reality (VR) causes arm fatigue and discomfort, negatively affecting user experience. Incorporating ergonomic considerations into VR user i…

cs.CV2026

Distill3R: A Pipeline for Democratizing 3D Foundation Models on Commodity Hardware

Brandon Leblanc, Charalambos Poullis

While multi-view 3D reconstruction has shifted toward large-scale foundation models capable of inferring globally consistent geometry, their reliance on massive computational clust…

cs.CV2025

Extreme Views: 3DGS Filter for Novel View Synthesis from Out-of-Distribution Camera Poses

Damian Bowness, Charalambos Poullis

When viewing a 3D Gaussian Splatting (3DGS) model from camera positions significantly outside the training data distribution, substantial visual noise commonly occurs. These artifa…

cs.CV2025

Fast Self-Supervised depth and mask aware Association for Multi-Object Tracking

Milad Khanchi, Maria Amer, Charalambos Poullis

Multi-object tracking (MOT) methods often rely on Intersection-over-Union (IoU) for association. However, this becomes unreliable when objects are similar or occluded. Also, comput…

cs.CV2025

Depth-Aware Scoring and Hierarchical Alignment for Multiple Object Tracking

Milad Khanchi, Maria Amer, Charalambos Poullis

Current motion-based multiple object tracking (MOT) approaches rely heavily on Intersection-over-Union (IoU) for object association. Without using 3D features, they are ineffective…