PoliTO-IIT Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition

07/01/2021
by   Chiara Plizzari, et al.
0

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 domain-shift which exists under the UDA setting, we first exploited a recent Domain Generalization (DG) technique, called Relative Norm Alignment (RNA). It consists in designing a model able to generalize well to any unseen domain, regardless of the possibility to access target data at training time. Then, in a second phase, we extended the approach to work on unlabelled target data, allowing the model to adapt to the target distribution in an unsupervised fashion. For this purpose, we included in our framework existing UDA algorithms, such as Temporal Attentive Adversarial Adaptation Network (TA3N), jointly with new multi-stream consistency losses, namely Temporal Hard Norm Alignment (T-HNA) and Min-Entropy Consistency (MEC). Our submission (entry 'plnet') is visible on the leaderboard and it achieved the 1st position for 'verb', and the 3rd position for both 'noun' and 'action'.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/09/2022

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 t...
research
01/29/2023

Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2022

In this report, we present the technical details of our submission to th...
research
07/24/2023

EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge: Mixed Sequences Prediction

This report presents the technical details of our approach for the EPIC-...
research
10/19/2021

Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition

First person action recognition is becoming an increasingly researched a...
research
07/13/2023

A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2023

In this technical report, we present our findings from a study conducted...
research
06/03/2022

Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2021

In this report, we present the technical details of our approach to the ...
research
04/12/2022

On the Equity of Nuclear Norm Maximization in Unsupervised Domain Adaptation

Nuclear norm maximization has shown the power to enhance the transferabi...

Please sign up or login with your details

Forgot password? Click here to reset