6 citations · 17 across the 11 of their papers we have counts for
12 papers
FS-SAM2: Adapting Segment Anything Model 2 for Few-Shot Semantic Segmentation via Low-Rank Adaptation
Bernardo Forni, Gabriele Lombardi, Federico Pozzi +1
Few-shot semantic segmentation has recently attracted great attention. The goal is to develop a model capable of segmenting unseen classes using only a few annotated samples. Most…
Egocentric zone-aware action recognition across environments
Simone Alberto Peirone, Gabriele Goletto, Mirco Planamente +3
Human activities exhibit a strong correlation between actions and the places where these are performed, such as washing something at a sink. More specifically, in daily living envi…
Bringing Online Egocentric Action Recognition into the wild
Gabriele Goletto, Mirco Planamente, Barbara Caputo +1
To enable a safe and effective human-robot cooperation, it is crucial to develop models for the identification of human activities. Egocentric vision seems to be a viable solution…
PoliTO-IIT-CINI Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition
Mirco Planamente, Gabriele Goletto, Gabriele Trivigno +2
In this report, we describe the technical details of our submission to the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition. To tackle the dom…
E(GO)MOTION: Motion Augmented Event Stream for Egocentric Action Recognition
Chiara Plizzari, Mirco Planamente, Gabriele Goletto +4
Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". Due to their sensing mechanism, event cameras have…
Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition
Mirco Planamente, Chiara Plizzari, Emanuele Alberti +1
First person action recognition is becoming an increasingly researched area thanks to the rising popularity of wearable cameras. This is bringing to light cross-domain issues that…
PoliTO-IIT Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition
Chiara Plizzari, Mirco Planamente, Emanuele Alberti +1
In this report, we describe the technical details of our submission to the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition. To tackle the dom…
Cross-Domain First Person Audio-Visual Action Recognition through Relative Norm Alignment
Mirco Planamente, Chiara Plizzari, Emanuele Alberti +1
First person action recognition is an increasingly researched topic because of the growing popularity of wearable cameras. This is bringing to light cross-domain issues that are ye…
DA4Event: towards bridging the Sim-to-Real Gap for Event Cameras using Domain Adaptation
Mirco Planamente, Chiara Plizzari, Marco Cannici +5
Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". The innovative way they acquire data presents seve…
Self-Supervised Joint Encoding of Motion and Appearance for First Person Action Recognition
Mirco Planamente, Andrea Bottino, Barbara Caputo
Wearable cameras are becoming more and more popular in several applications, increasing the interest of the research community in developing approaches for recognizing actions from…
A recurrent multi-scale approach to RBG-D Object Recognition
Mirco Planamente, Mohammad Reza Loghmani, Barbara Caputo
Technological development aims to produce generations of increasingly efficient robots able to perform complex tasks. This requires considerable efforts, from the scientific commun…
Recurrent Convolutional Fusion for RGB-D Object Recognition
Mohammad Reza Loghmani, Mirco Planamente, Barbara Caputo +1
Providing machines with the ability to recognize objects like humans has always been one of the primary goals of machine vision. The introduction of RGB-D cameras has paved the way…