57 citations · 80 across the 7 of their papers we have counts for
7 papers
The Robust Semantic Segmentation UNCV2023 Challenge Results
Xuanlong Yu, Yi Zuo, Zitao Wang +34
This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023. The challenge was centered around semantic segment…
Mask2Anomaly: Mask Transformer for Universal Open-set Segmentation
Shyam Nandan Rai, Fabio Cermelli, Barbara Caputo +1
Segmenting unknown or anomalous object instances is a critical task in autonomous driving applications, and it is approached traditionally as a per-pixel classification problem. Ho…
Reimagine BiSeNet for Real-Time Domain Adaptation in Semantic Segmentation
Antonio Tavera, Carlo Masone, Barbara Caputo
Semantic segmentation models have reached remarkable performance across various tasks. However, this performance is achieved with extremely large models, using powerful computation…
Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic Segmentation
Antonio Tavera, Fabio Cermelli, Carlo Masone +1
In this paper we consider the task of semantic segmentation in autonomous driving applications. Specifically, we consider the cross-domain few-shot setting where training can use o…
Viewpoint Invariant Dense Matching for Visual Geolocalization
Gabriele Berton, Carlo Masone, Valerio Paolicelli +1
In this paper we propose a novel method for image matching based on dense local features and tailored for visual geolocalization. Dense local features matching is robust against ch…
Adaptive-Attentive Geolocalization from few queries: a hybrid approach
Gabriele Moreno Berton, Valerio Paolicelli, Carlo Masone +1
We address the task of cross-domain visual place recognition, where the goal is to geolocalize a given query image against a labeled gallery, in the case where the query and the ga…
IDDA: a large-scale multi-domain dataset for autonomous driving
Emanuele Alberti, Antonio Tavera, Carlo Masone +1
Semantic segmentation is key in autonomous driving. Using deep visual learning architectures is not trivial in this context, because of the challenges in creating suitable large sc…