44 citations · 53 across the 6 of their papers we have counts for
7 papers · 1 filter
Self-supervised Monocular Depth Estimation: Let's Talk About The Weather
Kieran Saunders, George Vogiatzis, Luis Manso
Current, self-supervised depth estimation architectures rely on clear and sunny weather scenes to train deep neural networks. However, in many locations, this assumption is too str…
Multi-person 3D pose estimation from unlabelled data
Daniel Rodriguez-Criado, Pilar Bachiller, George Vogiatzis +1
Its numerous applications make multi-human 3D pose estimation a remarkably impactful area of research. Nevertheless, assuming a multiple-view system composed of several regular RGB…
Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps
Kieran Saunders, George Vogiatzis, Luis J. Manso
Self-supervised monocular depth estimation has been a subject of intense study in recent years, because of its applications in robotics and autonomous driving. Much of the recent w…
Look and Listen: A Multi-modality Late Fusion Approach to Scene Classification for Autonomous Machines
Jordan J. Bird, Diego R. Faria, Cristiano Premebida +2
The novelty of this study consists in a multi-modality approach to scene classification, where image and audio complement each other in a process of deep late fusion. The approach…
How to Read Paintings: Semantic Art Understanding with Multi-Modal Retrieval
Noa Garcia, George Vogiatzis
Automatic art analysis has been mostly focused on classifying artworks into different artistic styles. However, understanding an artistic representation involves more complex proce…
Dress like a Star: Retrieving Fashion Products from Videos
Noa Garcia, George Vogiatzis
This work proposes a system for retrieving clothing and fashion products from video content. Although films and television are the perfect showcase for fashion brands to promote th…
Learning Non-Metric Visual Similarity for Image Retrieval
Noa Garcia, George Vogiatzis
Measuring visual similarity between two or more instances within a data distribution is a fundamental task in image retrieval. Theoretically, non-metric distances are able to gener…