3 citations · 7 across the 3 of their papers we have counts for
9 papers · 1 filter
The revenge of BiSeNet: Efficient Multi-Task Image Segmentation
Gabriele Rosi, Claudia Cuttano, Niccolò Cavagnero +2
Recent advancements in image segmentation have focused on enhancing the efficiency of the models to meet the demands of real-time applications, especially on edge devices. However,…
Cross-Domain Transfer Learning with CoRTe: Consistent and Reliable Transfer from Black-Box to Lightweight Segmentation Model
Claudia Cuttano, Antonio Tavera, Fabio Cermelli +2
Many practical applications require training of semantic segmentation models on unlabelled datasets and their execution on low-resource hardware. Distillation from a trained source…
PEM: Prototype-based Efficient MaskFormer for Image Segmentation
Niccolò Cavagnero, Gabriele Rosi, Claudia Cuttano +4
Recent transformer-based architectures have shown impressive results in the field of image segmentation. Thanks to their flexibility, they obtain outstanding performance in multipl…
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…
Unmasking Anomalies in Road-Scene Segmentation
Shyam Nandan Rai, Fabio Cermelli, Dario Fontanel +2
Anomaly segmentation is a critical task for driving applications, and it is approached traditionally as a per-pixel classification problem. However, reasoning individually about ea…