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20182026
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cs.CV2026

EAST: Early Action Prediction Sampling Strategy with Token Masking

Iva Sović, Ivan Martinović, Marin Oršić

Early action prediction seeks to anticipate an action before it fully unfolds, but limited visual evidence makes this task especially challenging. We introduce EAST, a simple and e…

cs.CV2025

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…

cs.CV2021

Multi-domain semantic segmentation with overlapping labels

Petra Bevandić, Marin Oršić, Ivan Grubišić +2

Deep supervised models have an unprecedented capacity to absorb large quantities of training data. Hence, training on many datasets becomes a method of choice towards graceful degr…

cs.CV2019

Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift

Petra Bevandić, Ivan Krešo, Marin Oršić +1

Recent success on realistic road driving datasets has increased interest in exploring robust performance in real-world applications. One of the major unsolved problems is to identi…

cs.CV2019

Single Level Feature-to-Feature Forecasting with Deformable Convolutions

Josip Šarić, Marin Oršić, Tonći Antunović +2

Future anticipation is of vital importance in autonomous driving and other decision-making systems. We present a method to anticipate semantic segmentation of future frames in driv…

cs.CV2019

Pedestrian Tracking by Probabilistic Data Association and Correspondence Embeddings

Borna Bićanić, Marin Oršić, Ivan Marković +2

This paper studies the interplay between kinematics (position and velocity) and appearance cues for establishing correspondences in multi-target pedestrian tracking. We investigate…