activity
20172022
most citedDeep execution monitor for robot assistive tasks

6 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022★ 4 cited

Max Pooling with Vision Transformers reconciles class and shape in weakly supervised semantic segmentation

Simone Rossetti, Damiano Zappia, Marta Sanzari +2

Weakly Supervised Semantic Segmentation (WSSS) research has explored many directions to improve the typical pipeline CNN plus class activation maps (CAM) plus refinements, given th…

cs.AI2019★ 6 cited

Deep execution monitor for robot assistive tasks

Lorenzo Mauro, Edoardo Alati, Marta Sanzari +3

We consider a novel approach to high-level robot task execution for a robot assistive task. In this work we explore the problem of learning to predict the next subtask by introduci…

cs.AI2019★ 4 cited

Visual search and recognition for robot task execution and monitoring

Lorenzo Mauro, Francesco Puja, Simone Grazioso +4

Visual search of relevant targets in the environment is a crucial robot skill. We propose a preliminary framework for the execution monitor of a robot task, taking care of the robo…

cs.AI2017

Vision-based deep execution monitoring

Francesco Puja, Simone Grazioso, Antonio Tammaro +3

Execution monitor of high-level robot actions can be effectively improved by visual monitoring the state of the world in terms of preconditions and postconditions that hold before…

cs.RO2017

Discovery and recognition of motion primitives in human activities

Marta Sanzari, Valsamis Ntouskos, Fiora Pirri

We present a novel framework for the automatic discovery and recognition of motion primitives in videos of human activities. Given the 3D pose of a human in a video, human motion p…