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Found 12 papers, 5 papers with code
Bringing Online Egocentric Action Recognition into the wild
To enable a safe and effective human-robot cooperation, it is crucial to develop models for the identification of human activities.
PoliTO-IIT-CINI Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition
In this report, we describe the technical details of our submission to the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition.
E2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action Recognition
However, the ever-growing field of event-based vision has, to date, overlooked the potential of event cameras in such applications.
E$^2$(GO)MOTION: Motion Augmented Event Stream for Egocentric Action Recognition
However, the ever-growing field of event-based vision has, to date, overlooked the potential of event cameras in such applications.
Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition
First person action recognition is becoming an increasingly researched area thanks to the rising popularity of wearable cameras.
PoliTO-IIT Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition
In this report, we describe the technical details of our submission to the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition.
Cross-Domain First Person Audio-Visual Action Recognition through Relative Norm Alignment
First person action recognition is an increasingly researched topic because of the growing popularity of wearable cameras.
DA4Event: towards bridging the Sim-to-Real Gap for Event Cameras using Domain Adaptation
Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events".
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition
Unsupervised Domain Adaptation (DA) exploits the supervision of a label-rich source dataset to make predictions on an unlabeled target dataset by aligning the two data distributions.
Self-Supervised Joint Encoding of Motion and Appearance for First Person Action Recognition
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 the first-person point of view.
A recurrent multi-scale approach to RBG-D Object Recognition
Technological development aims to produce generations of increasingly efficient robots able to perform complex tasks.
Recurrent Convolutional Fusion for RGB-D Object Recognition
Providing machines with the ability to recognize objects like humans has always been one of the primary goals of machine vision.
