ITI-CERTH participation in ActEV and AVS Tracks of TRECVID 2022

Autor: Gkountakos, Konstantinos, Galanopoulos, Damianos, Touska, Despoina, Ioannidis, Konstantinos, Vrochidis, Stefanos, Mezaris, Vasileios, Kompatsiaris, Ioannis
Jazyk: angličtina
Rok vydání: 2023
Předmět:
DOI: 10.5281/zenodo.7431865
Popis: This report presents the overview of the runs related to Ad-hoc Video Search (AVS) and Activitiesin Extended Video (ActEV) tasks on behalf of the ITI-CERTH team. Our participation in the AVStask is based on a cross-modal deep network architecture utilizing several textual and visual features.As part of the retrieval stage, a dual-softmax approach is utilized to revise the calculated text-video similarities. For the ActEV task, we adapt our framework to fit the new dataset and overcome thechallenges of detecting and recognizing activities in a multi-label manner while experimenting withtwo separate activity classifiers.
Databáze: OpenAIRE