3 citations · 6 across the 10 of their papers we have counts for
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cs.CV2026
MC-PanDA++: Simpler, Stronger, and More Robust Domain-Adaptive Panoptic Segmentation
Ivan Martinović, Josip Šarić, Yuki M. Asano +1
Unsupervised domain adaptation (UDA) reduces the annotation burden in panoptic segmentation by leveraging a cost-effectively labeled source domain (e.g., synthetic) and an unlabele…
cs.CV2026
SPAR: Single-Pass Any-Resolution ViT for Open-vocabulary Segmentation
Naomi Kombol, Ivan Martinović, Siniša Šegvić +1
Foundational Vision Transformers (ViTs) have limited effectiveness in tasks requiring fine-grained spatial understanding, due to their fixed pre-training resolution and inherently…