Alam, Naushad 
ORCID: 0000-0002-3144-5622, Graham, Yvette ORCID: 0000-0001-6741-4855 and Gurrin, Cathal ORCID: 0000-0003-2903-3968
(2022)
Memento 2.0: an improved lifelog search engine for LSC’22.
In: 5th Annual Lifelog Search Challenge (LSC ’22), ICMR 2022, 27-30 June 2022, Newark, NJ, USA.
ISBN 978-1-4503-9239-6
Abstract
In this paper, we present Memento 2.0, an improved version of our
system which first participated in the Lifelog Search Challenge 2021.
Memento 2.0 employs image-text embeddings derived from two
CLIP models (ViT-L/14 and ResNet-50x64) and adopts a weighted
ensemble approach to derive a combined final ranking. Our approach significantly improves the performance over the baseline
LSC’21 system. We additionally make important updates to the
system’s user interface after analysing the shortcomings to make it
more efficient and better suited to the needs of the Lifelog Search
Challenge.
Metadata
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Event Type: | Workshop |
| Refereed: | Yes |
| Uncontrolled Keywords: | lifelog; semantic image representation |
| Subjects: | Computer Science > Information retrieval Computer Science > Multimedia systems Computer Science > Information storage and retrieval systems Computer Science > Lifelog |
| DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > INSIGHT Centre for Data Analytics |
| Published in: | Proceedings of the 5th Annual Lifelog Search Challenge (LSC’22). . Association for Computer Machinery (ACM). ISBN 978-1-4503-9239-6 |
| Publisher: | Association for Computer Machinery (ACM) |
| Official URL: | https://doi.org/10.1145/3512729.3533006 |
| Copyright Information: | © 2022 The Authors. |
| Funders: | Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289_P2, co-funded by the European Regional Development Fund |
| ID Code: | 28998 |
| Deposited On: | 13 Sep 2023 10:24 by Naushad Alam . Last Modified 13 Sep 2023 10:24 |
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