collaborators

13 papers

cs.CV2026

Seeing Through the Weights: Privacy Leakage in Scene Coordinate Regression

Oleksii Nasypanyi, Jaemin Cho, Utku Ozbulak +2

Scene Coordinate Regression (SCR) methods are increasingly adopted for visual localization. In these approaches, the scene is implicitly encoded within a neural network that regres…

eess.IV2025

SpurBreast: A Curated Dataset for Investigating Spurious Correlations in Real-world Breast MRI Classification

Jong Bum Won, Wesley De Neve, Joris Vankerschaver +1

Deep neural networks (DNNs) have demonstrated remarkable success in medical imaging, yet their real-world deployment remains challenging due to spurious correlations, where models…

cs.CV2025

When Tracking Fails: Analyzing Failure Modes of SAM2 for Point-Based Tracking in Surgical Videos

Woowon Jang, Jiwon Im, Juseung Choi +3

Video object segmentation (VOS) models such as SAM2 offer promising zero-shot tracking capabilities for surgical videos using minimal user input. Among the available input types, p…

cs.CV2025

Token-Based Detection of Spurious Correlations in Vision Transformers

Solha Kang, Esla Timothy Anzaku, Wesley De Neve +4

Due to their powerful feature association capabilities, neural network-based computer vision models have the ability to detect and exploit unintended patterns within the data, pote…

cs.CV2025

Improved Sub-Visible Particle Classification in Flow Imaging Microscopy via Generative AI-Based Image Synthesis

Utku Ozbulak, Michaela Cohrs, Hristo L. Svilenov +2

Sub-visible particle analysis using flow imaging microscopy combined with deep learning has proven effective in identifying particle types, enabling the distinction of harmless com…

cs.CV2025

Towards Affordable Tumor Segmentation and Visualization for 3D Breast MRI Using SAM2

Solha Kang, Eugene Kim, Joris Vankerschaver +1

Breast MRI provides high-resolution volumetric imaging critical for tumor assessment and treatment planning, yet manual interpretation of 3D scans remains labor-intensive and subje…