9 citations · 19 across the 14 of their papers we have counts for
6 papers · 1 filter
CLASH: A Benchmark for Cross-Modal Contradiction Detection
Teodora Popordanoska, Jiameng Li, Matthew B. Blaschko
Contradictory multimodal inputs are common in real-world settings, yet existing benchmarks typically assume input consistency and fail to evaluate cross-modal contradiction detecti…
Revisiting Reweighted Risk for Calibration: AURC, Focal, and Inverse Focal Loss
Han Zhou, Sebastian G. Gruber, Teodora Popordanoska +1
Several variants of reweighted risk functionals, such as focal loss, inverse focal loss, and the Area Under the Risk Coverage Curve (AURC), have been proposed for improving model c…
CARE: Confidence-aware Ratio Estimation for Medical Biomarkers
Jiameng Li, Teodora Popordanoska, Aleksei Tiulpin +3
Ratio-based biomarkers (RBBs), such as the proportion of necrotic tissue within a tumor, are widely used in clinical practice to support diagnosis, prognosis, and treatment plannin…
DAVE: Diagnostic benchmark for Audio Visual Evaluation
Gorjan Radevski, Teodora Popordanoska, Matthew B. Blaschko +1
Audio-visual understanding is a rapidly evolving field that seeks to integrate and interpret information from both auditory and visual modalities. Despite recent advances in multi-…
Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection
Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko
Despite their impressive predictive performance in various computer vision tasks, deep neural networks (DNNs) tend to make overly confident predictions, which hinders their widespr…
Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels
Zifu Wang, Teodora Popordanoska, Jeroen Bertels +2
The soft Dice loss (SDL) has taken a pivotal role in numerous automated segmentation pipelines in the medical imaging community. Over the last years, some reasons behind its superi…