3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CV2026★ 3 cited
Lightweight Neural Networks for Affordance Segmentation: Enhancement of the Decoder Module
Simone Lugani, Edoardo Ragusa, Rodolfo Zunino +1
The deployment of deep neural networks for visual affordance segmentation on wearable robots poses may prove critical, due to some conflicting aspects of the problem. On one hand,…
cs.CV2026★ 1 cited
Filling the Pareto-Optimal Front for Affordance Segmentation on Embedded Devices Using RGB-D Cameras
Edoardo Ragusa, Giovanni Paolo Canuti, Simone Lugani +2
While depth sensors have the potential to complement RGB data for affordance segmentation in wearable robots, their usage seems to remain underexplored. The paper proposes two appr…