8 papers · 1 filter
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…
What Holds Back Open-Vocabulary Segmentation?
Josip Šarić, Ivan Martinović, Matej Kristan +1
Standard segmentation setups are unable to deliver models that can recognize concepts outside the training taxonomy. Open-vocabulary approaches promise to close this gap through la…
DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation
Ivan Martinović, Josip Šarić, Marin Oršić +2
Pixel-level annotation is expensive and time-consuming. Semi-supervised segmentation methods address this challenge by learning models on few labeled images alongside a large corpu…
Sequential keypoint density estimator: an overlooked baseline of skeleton-based video anomaly detection
Anja Delić, Matej Grcić, Siniša Šegvić
Detecting anomalous human behaviour is an important visual task in safety-critical applications such as healthcare monitoring, workplace safety, or public surveillance. In these co…
A Survey on Training-free Open-Vocabulary Semantic Segmentation
Naomi Kombol, Ivan Martinović, Siniša Šegvić
Semantic segmentation is one of the most fundamental tasks in image understanding with a long history of research, and subsequently a myriad of different approaches. Traditional me…
MC-PanDA: Mask Confidence for Panoptic Domain Adaptation
Ivan Martinović, Josip Šarić, Siniša Šegvić
Domain adaptive panoptic segmentation promises to resolve the long tail of corner cases in natural scene understanding. Previous state of the art addresses this problem with cross-…